{"id":3488,"date":"2025-09-02T11:12:58","date_gmt":"2025-09-02T09:12:58","guid":{"rendered":"https:\/\/neuraldesigner.com\/learning\/examples-dermatology\/"},"modified":"2026-02-11T12:01:32","modified_gmt":"2026-02-11T11:01:32","slug":"examples-dermatology","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/examples\/examples-dermatology\/","title":{"rendered":"Diagnose dermatological diseases using machine learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3488\" class=\"elementor elementor-3488\" data-elementor-post-type=\"learning\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4ac57b3c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4ac57b3c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-14a26bd3\" data-id=\"14a26bd3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8cc0461 elementor-widget elementor-widget-heading\" data-id=\"8cc0461\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Introduction<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8e9be29 elementor-widget elementor-widget-text-editor\" data-id=\"8e9be29\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\" data-start=\"159\" data-end=\"386\">Machine learning is enhancing dermatological diagnosis by improving accuracy in identifying erythemato-squamous diseases (ESDs), which often share overlapping clinical and microscopic features.<\/p><p style=\"text-align: justify;\" data-start=\"159\" data-end=\"386\">Accurate classification is key to effective treatment. We implemented a neural network using clinical and histopathological data from 366 patients, achieving 98.6% accuracy and demonstrating strong potential as a decision-support tool for distinguishing ESDs.<\/p><p style=\"text-align: justify;\" data-start=\"159\" data-end=\"386\">Healthcare professionals can test this methodology by downloading Neural Designer.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-dedf628 e-flex e-con-boxed e-con e-parent\" data-id=\"dedf628\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f97579c elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"f97579c\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.neuraldesigner.com\/downloads\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-icon\">\n\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-download\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M216 0h80c13.3 0 24 10.7 24 24v168h87.7c17.8 0 26.7 21.5 14.1 34.1L269.7 378.3c-7.5 7.5-19.8 7.5-27.3 0L90.1 226.1c-12.6-12.6-3.7-34.1 14.1-34.1H192V24c0-13.3 10.7-24 24-24zm296 376v112c0 13.3-10.7 24-24 24H24c-13.3 0-24-10.7-24-24V376c0-13.3 10.7-24 24-24h146.7l49 49c20.1 20.1 52.5 20.1 72.6 0l49-49H488c13.3 0 24 10.7 24 24zm-124 88c0-11-9-20-20-20s-20 9-20 20 9 20 20 20 20-9 20-20zm64 0c0-11-9-20-20-20s-20 9-20 20 9 20 20 20 20-9 20-20z\"><\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1e68242 elementor-widget elementor-widget-heading\" data-id=\"1e68242\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Contents<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43625e9 elementor-widget elementor-widget-text-editor\" data-id=\"43625e9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The following index outlines the steps for performing the analysis.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-af1111b e-grid e-con-boxed e-con e-parent\" data-id=\"af1111b\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e34729c elementor-align-center elementor-widget elementor-widget-button\" data-id=\"e34729c\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#model_type\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">1.Model type<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9af7c61 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"9af7c61\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#dataset\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">2.Dataset<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8ccf9be elementor-align-center elementor-widget elementor-widget-button\" data-id=\"8ccf9be\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#neural_network\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">3.Neural network<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-65bfc91 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"65bfc91\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#training_strategy\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">4.Training strategy<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cf8e22 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"5cf8e22\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#model_selection\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">5.Model selection<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a700496 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"a700496\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#testing_analysis\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">6.Testing analysis<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b8b21fa elementor-align-center elementor-widget elementor-widget-button\" data-id=\"b8b21fa\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#model_deployment\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">7.Model deployment<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c623e5 elementor-widget elementor-widget-heading\" data-id=\"5c623e5\" data-element_type=\"widget\" id=\"model_type\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">1. Model type<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-108748e elementor-widget elementor-widget-text-editor\" data-id=\"108748e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li data-start=\"48\" data-end=\"147\" style=\"text-align: justify;\"><strong data-start=\"48\" data-end=\"65\">Problem type:<\/strong> Multiclass <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-networks-applications#Classification\">classification<\/a> (type of ESD: psoriasis, seborrheic dermatitis, etc.)<\/li>\n \t<li data-start=\"48\" data-end=\"147\" style=\"text-align: justify;\"><strong data-start=\"149\" data-end=\"158\">Goal:<\/strong> Model the probability of each ESD type based on patient features and clinical variables to support diagnostic decision-making using artificial intelligence and machine learning.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f1b87ca elementor-widget elementor-widget-heading\" data-id=\"f1b87ca\" data-element_type=\"widget\" id=\"dataset\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">2. Data set<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6551a95 elementor-widget elementor-widget-text-editor\" data-id=\"6551a95\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Data source<\/h3>\n<p style=\"text-align: justify;\">The dermatology.csv dataset contains 366 instances and 35 variables for this example.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9b3a1ff e-flex e-con-boxed e-con e-parent\" data-id=\"9b3a1ff\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1350d2f elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"1350d2f\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/dermatology.csv\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-icon\">\n\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-file-download\" viewBox=\"0 0 384 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M224 136V0H24C10.7 0 0 10.7 0 24v464c0 13.3 10.7 24 24 24h336c13.3 0 24-10.7 24-24V160H248c-13.2 0-24-10.8-24-24zm76.45 211.36l-96.42 95.7c-6.65 6.61-17.39 6.61-24.04 0l-96.42-95.7C73.42 337.29 80.54 320 94.82 320H160v-80c0-8.84 7.16-16 16-16h32c8.84 0 16 7.16 16 16v80h65.18c14.28 0 21.4 17.29 11.27 27.36zM377 105L279.1 7c-4.5-4.5-10.6-7-17-7H256v128h128v-6.1c0-6.3-2.5-12.4-7-16.9z\"><\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Dataset<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb35475 elementor-widget elementor-widget-heading\" data-id=\"eb35475\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Variables<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2108fe3 elementor-widget elementor-widget-text-editor\" data-id=\"2108fe3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The following list summarizes the variables&#8217; information:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73d54d4 elementor-widget elementor-widget-heading\" data-id=\"73d54d4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Clinical features (0\u20133)<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3077f0b elementor-widget elementor-widget-text-editor\" data-id=\"3077f0b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"655\" data-end=\"1301\"><li style=\"text-align: justify;\" data-start=\"655\" data-end=\"687\"><p data-start=\"657\" data-end=\"687\"><strong data-start=\"657\" data-end=\"669\">rythema<\/strong> \u2013 Skin redness.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"688\" data-end=\"717\"><p data-start=\"690\" data-end=\"717\"><strong data-start=\"690\" data-end=\"701\">scaling<\/strong> \u2013 Scaly skin.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"718\" data-end=\"812\"><p data-start=\"720\" data-end=\"812\"><strong data-start=\"720\" data-end=\"740\">definite_borders<\/strong> \u2013 Clear and sharp border separating the lesion from its surroundings.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"813\" data-end=\"882\"><p data-start=\"815\" data-end=\"882\"><strong data-start=\"815\" data-end=\"826\">itching<\/strong> \u2013 Unpleasant skin sensation that provokes scratching.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"883\" data-end=\"977\"><p data-start=\"885\" data-end=\"977\"><strong>koebner phenomenon<\/strong> \u2013 New lesions appearing on areas of trauma in predisposed patients.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"978\" data-end=\"1042\"><p data-start=\"980\" data-end=\"1042\"><strong data-start=\"980\" data-end=\"1001\">polygonal_papules<\/strong> \u2013 Shiny, flat-topped, firm elevations.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1043\" data-end=\"1119\"><p data-start=\"1045\" data-end=\"1119\"><strong data-start=\"1045\" data-end=\"1067\">follicular_papules<\/strong> \u2013 Small, solid, circumscribed elevations (&lt;1 cm).<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1120\" data-end=\"1180\"><p data-start=\"1122\" data-end=\"1180\"><strong data-start=\"1122\" data-end=\"1150\">oral_mucosal_involvement<\/strong> \u2013 Lesions inside the mouth.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1181\" data-end=\"1251\"><p data-start=\"1183\" data-end=\"1251\"><strong data-start=\"1183\" data-end=\"1213\">knee and elbow involvement<\/strong> \u2013 Lesions on the knee and\/or elbow.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1252\" data-end=\"1301\"><p data-start=\"1254\" data-end=\"1301\"><strong data-start=\"1254\" data-end=\"1275\">scalp_involvement<\/strong> \u2013 Lesions on the scalp.<\/p><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-285ecd9 elementor-widget elementor-widget-heading\" data-id=\"285ecd9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Demographic and family history<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3843c2e elementor-widget elementor-widget-text-editor\" data-id=\"3843c2e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"1340\" data-end=\"1488\">\n \t<li data-start=\"1340\" data-end=\"1446\" style=\"text-align: justify;\">\n<p data-start=\"1342\" data-end=\"1446\"><strong data-start=\"1342\" data-end=\"1369\">family_history (0 or 1)<\/strong> \u2013 Presence (1) or absence (0) of family history of dermatological disease.<\/p>\n<\/li>\n \t<li data-start=\"1447\" data-end=\"1488\" style=\"text-align: justify;\">\n<p data-start=\"1449\" data-end=\"1488\"><strong data-start=\"1449\" data-end=\"1464\">age (years)<\/strong> \u2013 Age of the patient.<\/p>\n<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5bb78f0 elementor-widget elementor-widget-heading\" data-id=\"5bb78f0\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Histopathological features (0\u20133)<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-092f6d0 elementor-widget elementor-widget-text-editor\" data-id=\"092f6d0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"1529\" data-end=\"3094\"><li style=\"text-align: justify;\" data-start=\"1529\" data-end=\"1603\"><p data-start=\"1531\" data-end=\"1603\"><strong data-start=\"1531\" data-end=\"1555\">melanin_incontinence<\/strong> \u2013 Spillage of melanin into connective tissue.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1604\" data-end=\"1677\"><p data-start=\"1606\" data-end=\"1677\"><strong data-start=\"1606\" data-end=\"1632\">eosinophils_infiltrate<\/strong> \u2013 Eosinophils infiltrating skin or mucosa.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1678\" data-end=\"1746\"><p data-start=\"1680\" data-end=\"1746\"><strong data-start=\"1680\" data-end=\"1698\">pnl_infiltrate<\/strong> \u2013 Enlarged nerve trunks without skin lesions.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1747\" data-end=\"1820\"><p data-start=\"1749\" data-end=\"1820\"><strong data-start=\"1749\" data-end=\"1781\">fibrosis_of_papillary_dermis<\/strong> \u2013 Excess fibrous tissue development.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1821\" data-end=\"1886\"><p data-start=\"1823\" data-end=\"1886\"><strong data-start=\"1823\" data-end=\"1837\">exocytosis<\/strong> \u2013 Passage of foreign cells into the epidermis.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1887\" data-end=\"1939\"><p data-start=\"1889\" data-end=\"1939\"><strong data-start=\"1889\" data-end=\"1903\">acanthosis<\/strong> \u2013 Thickened, darkened skin areas.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"1940\" data-end=\"2000\"><p data-start=\"1942\" data-end=\"2000\"><strong data-start=\"1942\" data-end=\"1960\">hyperkeratosis<\/strong> \u2013 Thickening of the outer skin layer.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2001\" data-end=\"2068\"><p data-start=\"2003\" data-end=\"2068\"><strong data-start=\"2003\" data-end=\"2020\">parakeratosis<\/strong> \u2013 Retention of nuclei in the stratum corneum.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2069\" data-end=\"2157\"><p data-start=\"2071\" data-end=\"2157\"><strong>clubbing of rete ridges<\/strong> \u2013 Enlarged epithelial extensions into connective tissue.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2158\" data-end=\"2221\"><p data-start=\"2160\" data-end=\"2221\"><strong data-start=\"2160\" data-end=\"2189\">elongation_of_rete_ridges<\/strong> \u2013 Lengthening of rete ridges.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2222\" data-end=\"2296\"><p data-start=\"2224\" data-end=\"2296\"><strong data-start=\"2224\" data-end=\"2264\">thinning of suprapapillary epidermis<\/strong> \u2013 Thinning at papillary tips.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2297\" data-end=\"2373\"><p data-start=\"2299\" data-end=\"2373\"><strong data-start=\"2299\" data-end=\"2321\">spongiform_pustule<\/strong> \u2013 Epidermal pustule with neutrophil infiltration.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2374\" data-end=\"2464\"><p data-start=\"2376\" data-end=\"2464\"><strong data-start=\"2376\" data-end=\"2397\">munro_microabcess<\/strong> \u2013 Abscess in the stratum corneum due to neutrophil infiltration.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2465\" data-end=\"2522\"><p data-start=\"2467\" data-end=\"2522\"><strong data-start=\"2467\" data-end=\"2492\">focal_hypergranulosis<\/strong> \u2013 Thickened granular layer.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2523\" data-end=\"2597\"><p data-start=\"2525\" data-end=\"2597\"><strong>disappearance of the granular layer<\/strong> \u2013 Loss of the skin granular layer.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2598\" data-end=\"2684\"><p data-start=\"2600\" data-end=\"2684\"><strong data-start=\"2600\" data-end=\"2634\">vacuolisation and basal damage<\/strong> \u2013 Vacuolization and damage in basal skin cells.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2685\" data-end=\"2726\"><p data-start=\"2687\" data-end=\"2726\"><strong data-start=\"2687\" data-end=\"2701\">spongiosis<\/strong> \u2013 Intercellular edema.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2727\" data-end=\"2800\"><p data-start=\"2729\" data-end=\"2800\"><strong>saw-tooth appearance of retes<\/strong> \u2013 Saw-tooth pattern of rete ridges.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2801\" data-end=\"2861\"><p data-start=\"2803\" data-end=\"2861\"><strong data-start=\"2803\" data-end=\"2827\">follicular_horn_plug<\/strong> \u2013 Presence of follicular plugs.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2862\" data-end=\"2934\"><p data-start=\"2864\" data-end=\"2934\"><strong data-start=\"2864\" data-end=\"2896\">perifollicular_parakeratosis<\/strong> \u2013 Retained nuclei around follicles.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"2935\" data-end=\"3015\"><p data-start=\"2937\" data-end=\"3015\"><strong data-start=\"2937\" data-end=\"2976\">inflammatory mononuclear infiltrate<\/strong> \u2013 Infiltration by mononuclear cells.<\/p><\/li><li style=\"text-align: justify;\" data-start=\"3016\" data-end=\"3094\"><p data-start=\"3018\" data-end=\"3094\"><strong data-start=\"3018\" data-end=\"3042\">band_like_infiltrate<\/strong> \u2013 Banded infiltration pattern in basal epidermis.<\/p><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-451d638 elementor-widget elementor-widget-heading\" data-id=\"451d638\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Target variable<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1fdc272 elementor-widget elementor-widget-text-editor\" data-id=\"1fdc272\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"3118\" data-end=\"3315\">\n \t<li data-start=\"3118\" data-end=\"3315\" style=\"text-align: justify;\">\n<p data-start=\"3120\" data-end=\"3172\"><strong data-start=\"3120\" data-end=\"3146\">diagnose (categorical) &#8211;<\/strong> six possible classes (Psoriasis, Seborreic dermatitis, Lichen planus, Pityriasis rosea, Chronic dermatitis, and Pityriasis rubra pilaris)<\/p>\n<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9ab63a9 elementor-widget elementor-widget-text-editor\" data-id=\"9ab63a9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Instances<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b3f3587 elementor-widget elementor-widget-text-editor\" data-id=\"b3f3587\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The dataset\u2019s\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#Instances\">instances<\/a> are split into training (60%), validation (20%), and testing (20%) subsets by default.<\/p>\n\n<p style=\"text-align: justify;\">You can adjust them as needed.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-627c19d elementor-widget elementor-widget-text-editor\" data-id=\"627c19d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Variables distributions<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f6ca2f elementor-widget elementor-widget-text-editor\" data-id=\"0f6ca2f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\" >We can calculate variable <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#Distributions\">distributions<\/a>; the figure shows a chart with the number of cases for each dermatological condition in the dataset.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2d3a285 elementor-widget elementor-widget-image\" data-id=\"2d3a285\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"635\" height=\"380\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/diagnose-distribution-pie-chart.png\" class=\"attachment-large size-large wp-image-19710\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/diagnose-distribution-pie-chart.png 635w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/diagnose-distribution-pie-chart-300x180.png 300w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/diagnose-distribution-pie-chart-600x359.png 600w\" sizes=\"(max-width: 635px) 100vw, 635px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-47246f5 elementor-widget elementor-widget-text-editor\" data-id=\"47246f5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">Psoriasis accounts for 30.6% of the samples, while pityriasis rubra pilaris represents the smallest proportion at 5.5%.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-273b6de elementor-widget elementor-widget-text-editor\" data-id=\"273b6de\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3>Input-target correlations<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f45e0e elementor-widget elementor-widget-text-editor\" data-id=\"4f45e0e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#InputsTargetsCorrelations\">input-target correlations<\/a> indicate which clinical or diagnostic factors most influence each dermatological condition and, therefore, are more relevant to our analysis.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2b572c2 elementor-widget elementor-widget-image\" data-id=\"2b572c2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"600\" height=\"694\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/correlations-derma.webp\" class=\"attachment-large size-large wp-image-16509\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/correlations-derma.webp 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/correlations-derma-259x300.webp 259w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4130842 elementor-widget elementor-widget-text-editor\" data-id=\"4130842\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">Here, the most correlated variables with malignant tumors are\u00a0<b>follicular horn plug<\/b>,\u00a0<b>follicular papules<\/b>, and\u00a0<b>elongation of the rete ridges<\/b>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43805a4 elementor-widget elementor-widget-heading\" data-id=\"43805a4\" data-element_type=\"widget\" id=\"neural_network\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">3. Neural network<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-384d539 elementor-widget elementor-widget-text-editor\" data-id=\"384d539\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">A neural network is an artificial intelligence model inspired by how the human brain processes information.<\/p>\n\n<p style=\"text-align: justify;\">It is organized in layers: the input layer receives the variables, the hidden layers combine them to detect relevant patterns, and the output layer provides the probability of belonging to a given class.<\/p>\n\n<p style=\"text-align: justify;\">Trained with historical data, the network learns to recognize patterns and distinguish between categories, offering objective support for decision-making.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c225e29 elementor-widget elementor-widget-image\" data-id=\"c225e29\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"388\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6-1024x497.png\" class=\"attachment-large size-large wp-image-19653\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6-1024x497.png 1024w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6-300x145.png 300w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6-768x372.png 768w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6-600x291.png 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/09\/Network-architecture-6.png 1093w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c5a2d99 elementor-widget elementor-widget-text-editor\" data-id=\"c5a2d99\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The network combines multiple inputs in a hidden layer to produce six outputs corresponding to different dermatological conditions, with connections showing each variable\u2019s contribution.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3041f06 elementor-widget elementor-widget-heading\" data-id=\"3041f06\" data-element_type=\"widget\" id=\"training_strategy\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">4. Training strategy<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e9f0a5 elementor-widget elementor-widget-text-editor\" data-id=\"3e9f0a5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">Training a neural network uses a loss function to measure errors and an optimization algorithm to update the model, enabling it to learn from data while avoiding overfitting and performing well on new, unseen cases.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3a5747f elementor-widget elementor-widget-image\" data-id=\"3a5747f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"600\" height=\"400\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/quasi-newton-derma.webp\" class=\"attachment-large size-large wp-image-16507\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/quasi-newton-derma.webp 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/quasi-newton-derma-300x200.webp 300w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fcda714 elementor-widget elementor-widget-text-editor\" data-id=\"fcda714\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The model was trained for both accuracy and stability, with training and selection errors steadily decreasing (0.01 and 0.09 WSE), indicating effective learning and strong generalization to new instances.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-94f138d elementor-widget elementor-widget-heading\" data-id=\"94f138d\" data-element_type=\"widget\" id=\"model_selection\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">5. Model selection<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e29d33 elementor-widget elementor-widget-text-editor\" data-id=\"5e29d33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The objective of <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection\">model selection<\/a> is to find the network architecture with the best generalization properties (that minimizes the error on the <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#SelectionInstances\">selected instances<\/a> of the data set).<\/p>\n\n<p style=\"text-align: justify;\">We\u00a0<span style=\"margin: 0px; padding: 0px;\">aim to develop a neural network with a selection error of less than\u00a0<strong>0.09 WSE<\/strong>, which is\u00a0<\/span>the value we have achieved so far.<\/p>\n\n<p style=\"text-align: justify;\"><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection\">Model selection<\/a> algorithms train several network architectures with a different number of neurons and select the one with the smallest selection error.<\/p>\n\n<p style=\"text-align: justify;\">The <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection#NeuronsSelection\">neural selection<\/a> method starts with a few neurons and increases the complexity at each iteration.\n\nThe following chart shows the training error (blue) and the selection error (orange) as a function of the number of neurons.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-467c3cd elementor-widget elementor-widget-image\" data-id=\"467c3cd\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"600\" height=\"400\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/Growing-derma.webp\" class=\"attachment-large size-large wp-image-16506\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/Growing-derma.webp 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/Growing-derma-300x200.webp 300w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62f0a59 elementor-widget elementor-widget-text-editor\" data-id=\"62f0a59\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">It shows that neuron selection does not significantly decrease the training error. But still, we obtained a minor error rate with four neurons.<\/p>\n\n<p style=\"text-align: justify;\"><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection#InputsSelection\">input selection<\/a> algorithms identify the subset of features that minimizes selection error and maximizes the network\u2019s generalization capability.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b5d74c elementor-widget elementor-widget-image\" data-id=\"7b5d74c\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"600\" height=\"400\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/input-selection-derma.webp\" class=\"attachment-large size-large wp-image-16505\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/input-selection-derma.webp 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/input-selection-derma-300x200.webp 300w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-06eaa85 elementor-widget elementor-widget-text-editor\" data-id=\"06eaa85\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">After selecting the optimal 30 inputs (4 unused), the model\u2019s selection error dropped to 0.03 WSE, yielding a simpler, improved network with architecture 30:3:6 (inputs:hidden:outputs).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e138632 elementor-widget elementor-widget-heading\" data-id=\"e138632\" data-element_type=\"widget\" id=\"testing_analysis\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">6. Testing analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-beb4d06 elementor-widget elementor-widget-text-editor\" data-id=\"beb4d06\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">Once we have trained the model, we perform a <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\">testing analysis<\/a> to validate its prediction capacity.<\/p>\n\n<p style=\"text-align: justify;\">We use a subset of previously unused data, specifically the <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#TestingInstances\">testing instances<\/a>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-129af1a elementor-widget elementor-widget-heading\" data-id=\"129af1a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Confusion matrix<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a48c8be elementor-widget elementor-widget-text-editor\" data-id=\"a48c8be\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\">The <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis#ConfusionMatrix\">confusion matrix<\/a> shows the model\u2019s performance by comparing predicted and actual diagnoses. It includes:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ea8ecfb elementor-widget elementor-widget-text-editor\" data-id=\"ea8ecfb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li data-start=\"197\" data-end=\"271\" style=\"text-align: justify;\">\n<p data-start=\"199\" data-end=\"271\"><strong data-start=\"199\" data-end=\"218\">True positives:<\/strong> cases correctly identified as having the condition<\/p>\n<\/li>\n \t<li data-start=\"272\" data-end=\"349\" style=\"text-align: justify;\">\n<p data-start=\"274\" data-end=\"349\"><strong data-start=\"274\" data-end=\"294\">False positives:<\/strong> cases incorrectly identified as having the condition<\/p>\n<\/li>\n \t<li data-start=\"350\" data-end=\"439\" style=\"text-align: justify;\">\n<p data-start=\"352\" data-end=\"439\"><strong data-start=\"352\" data-end=\"372\">False negatives:<\/strong> cases with the condition incorrectly identified as not having it<\/p>\n<\/li>\n \t<li data-start=\"440\" data-end=\"521\" style=\"text-align: justify;\">\n<p data-start=\"442\" data-end=\"521\"><strong data-start=\"442\" data-end=\"461\">True negatives:<\/strong> cases correctly identified as not having the condition<\/p>\n<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1b1a328 e-flex e-con-boxed e-con e-parent\" data-id=\"1b1a328\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2b579a9 elementor-widget elementor-widget-text-editor\" data-id=\"2b579a9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<div class=\"tabla-responsive\"><table class=\"mi-tabla\"><tbody><tr><th>\u00a0<\/th><th>Predicted seboreic dermatitis<\/th><th>Predicted soriasis<\/th><th>Predicted lichen planus<\/th><th>Predicted chronic dermatitis<\/th><th>Predicted pityriasis rosea<\/th><th>Predicted rubra pilaris<\/th><\/tr><tr><th style=\"text-align: left;\">Real seboreic dermatitis<\/th><td style=\"text-align: right;\">10<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><\/tr><tr><th style=\"text-align: left;\">Real soriasis<\/th><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">24<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><\/tr><tr><th style=\"text-align: left;\">Real lichen planus<\/th><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">15<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><\/tr><tr><th style=\"text-align: left;\">Real chronic dermatitis<\/th><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">11<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><\/tr><tr><th style=\"text-align: left;\">Real pityriasis rosea<\/th><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">9<\/td><td style=\"text-align: right;\">0<\/td><\/tr><tr><th style=\"text-align: left;\">Real pitiriasis rubra pilaris<\/th><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">0<\/td><td style=\"text-align: right;\">3<\/td><\/tr><\/tbody><\/table><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7138228 elementor-widget elementor-widget-text-editor\" data-id=\"7138228\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify;\"><span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">In this example, <strong>98.63%<\/strong> of cases were <strong>correctly classified<\/strong>\u00a0and\u00a0<strong>1.37%<\/strong>\u00a0 of cases were <strong>misclassified<\/strong>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9450ea5 elementor-widget elementor-widget-heading\" data-id=\"9450ea5\" data-element_type=\"widget\" id=\"model_deployment\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">7. Model deployment<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-255cd35 elementor-widget elementor-widget-text-editor\" data-id=\"255cd35\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"441\" data-end=\"717\" style=\"text-align: justify;\">Once validated, the neural network can be saved for deployment, allowing predictions of dermatological conditions for new patients using clinical, histopathological, demographic, and lesion data.<\/p>\n<p data-start=\"441\" data-end=\"717\" style=\"text-align: justify;\">It serves as a reliable diagnostic support tool, complements traditional examinations, and integrates easily via <a href=\"https:\/\/www.neuraldesigner.com\/my-account\/\">Neural Designer<\/a>, though the network cannot be practically visualized due to many input variables.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1b5aabe e-flex e-con-boxed e-con e-parent\" data-id=\"1b5aabe\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5ee60c1 elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"5ee60c1\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.neuraldesigner.com\/downloads\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-icon\">\n\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-download\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M216 0h80c13.3 0 24 10.7 24 24v168h87.7c17.8 0 26.7 21.5 14.1 34.1L269.7 378.3c-7.5 7.5-19.8 7.5-27.3 0L90.1 226.1c-12.6-12.6-3.7-34.1 14.1-34.1H192V24c0-13.3 10.7-24 24-24zm296 376v112c0 13.3-10.7 24-24 24H24c-13.3 0-24-10.7-24-24V376c0-13.3 10.7-24 24-24h146.7l49 49c20.1 20.1 52.5 20.1 72.6 0l49-49H488c13.3 0 24 10.7 24 24zm-124 88c0-11-9-20-20-20s-20 9-20 20 9 20 20 20 20-9 20-20zm64 0c0-11-9-20-20-20s-20 9-20 20 9 20 20 20 20-9 20-20z\"><\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4205efe elementor-widget elementor-widget-heading\" data-id=\"4205efe\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Conclusions<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-af2c28c elementor-widget elementor-widget-text-editor\" data-id=\"af2c28c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"254\" data-end=\"432\" style=\"text-align: justify;\">The dermatology machine learning model achieved 98.6% accuracy in classifying erythemato-squamous diseases.<\/p>\n<p data-start=\"254\" data-end=\"432\" style=\"text-align: justify;\">Key features\u2014like follicular horn plugs, follicular papules, and rete ridge elongation\u2014align with established dermatological criteria.<\/p>\n<p data-start=\"254\" data-end=\"432\" style=\"text-align: justify;\">Its strong generalization allows it to support clinicians in differentiating conditions quickly and reliably, complementing traditional examinations and improving patient care.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-66e4571 elementor-widget elementor-widget-heading\" data-id=\"66e4571\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">References<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-837e510 elementor-widget elementor-widget-text-editor\" data-id=\"837e510\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li style=\"text-align: justify;\">We have obtained the data for this problem from the <a href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/dermatology\">UCI Machine Learning Repository<\/a>.<\/li>\n \t<li style=\"text-align: justify;\">Nilsel Ilter, M.D., Ph.D., Gazi University, School of Medicine.<\/li>\n \t<li style=\"text-align: justify;\">H. Altay Guvenir, PhD., Bilkent University, Department of Computer Engineering and Information Science.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bd1e290 elementor-widget elementor-widget-heading\" data-id=\"bd1e290\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Related posts<\/h2>\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"author":13,"featured_media":2286,"template":"","categories":[29],"tags":[38],"class_list":["post-3488","learning","type-learning","status-publish","has-post-thumbnail","hentry","category-examples","tag-healthcare"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Diagnose dermatological diseases using machine learning<\/title>\n<meta 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