{"id":3482,"date":"2025-08-29T11:12:59","date_gmt":"2025-08-29T09:12:59","guid":{"rendered":"https:\/\/neuraldesigner.com\/learning\/diagnose-hcv\/"},"modified":"2025-12-09T10:25:20","modified_gmt":"2025-12-09T09:25:20","slug":"liver-disease","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/examples\/liver-disease\/","title":{"rendered":"Diagnose liver diseases using machine learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3482\" class=\"elementor elementor-3482\" data-elementor-post-type=\"learning\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-31f75630 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"31f75630\" 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-42a31322\" data-id=\"42a31322\" 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-a2b2efe elementor-widget elementor-widget-heading\" data-id=\"a2b2efe\" 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-ac17b6b elementor-widget elementor-widget-text-editor\" data-id=\"ac17b6b\" 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=\"171\" data-end=\"273\">Machine learning has improved early detection and clinical decision-making in liver disease.<\/p><p style=\"text-align: justify;\" data-start=\"275\" data-end=\"486\">Conditions such as Hepatitis C, Fibrosis, and Cirrhosis are common and can lead to serious complications if not detected early. Diagnosis often requires integrating multiple blood and urine biomarkers.<\/p><p style=\"text-align: justify;\" data-start=\"488\" data-end=\"615\">We implemented a neural network model using patient data and biochemical markers to classify stages of liver disease.<\/p><p style=\"text-align: justify;\" data-start=\"617\" data-end=\"769\">Trained with the Medical University of Hannover dataset, the model achieved high accuracy, showing potential as a diagnostic support tool.<\/p><p style=\"text-align: justify;\" data-start=\"771\" data-end=\"865\">Healthcare professionals can test this methodology by downloading Neural Designer\u2019s.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b56b37c e-flex e-con-boxed e-con e-parent\" data-id=\"b56b37c\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-8773bb0 e-con-full e-flex e-con e-child\" data-id=\"8773bb0\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c9fa9df elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"c9fa9df\" 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<\/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-b17a317 elementor-widget elementor-widget-heading\" data-id=\"b17a317\" 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-8400cd0 elementor-widget elementor-widget-text-editor\" data-id=\"8400cd0\" 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-69c1e2e e-grid e-con-boxed e-con e-parent\" data-id=\"69c1e2e\" 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-b2ad98c elementor-align-center elementor-widget elementor-widget-button\" data-id=\"b2ad98c\" 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-6b0b093 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"6b0b093\" 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-ce09f2c elementor-align-center elementor-widget elementor-widget-button\" data-id=\"ce09f2c\" 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-03cdfd8 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"03cdfd8\" 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-d3c8680 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"d3c8680\" 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\">5.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-ca5d88d elementor-align-center elementor-widget elementor-widget-button\" data-id=\"ca5d88d\" 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\">6.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-0154aa9 elementor-widget elementor-widget-text-editor\" data-id=\"0154aa9\" data-element_type=\"widget\" id=\"model_type\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h2>1. Model type<\/h2>\n<ul>\n \t<li style=\"text-align: justify;\"><strong data-start=\"48\" data-end=\"65\">Problem type:<\/strong> Multiclass classification (no disease, suspect disease, hepatitis C, fibrosis, cirrhosis)<\/li>\n \t<li style=\"text-align: justify;\"><strong data-start=\"158\" data-end=\"167\">Goal:<\/strong> Model the probability of each liver condition based on patient tests, including blood and urine analyses, to support clinical decision-making.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a034131 elementor-widget elementor-widget-heading\" data-id=\"a034131\" 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-4690e33 elementor-widget elementor-widget-text-editor\" data-id=\"4690e33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3 style=\"font-family: Outfit, sans-serif; color: #242424;\">Data source<\/h3>\n<p style=\"text-align: justify;\">The dataset hvcdat.csv includes 615 instances (rows) and 13 variables (columns), with target values: no disease, suspect disease, Hepatitis C, Fibrosis, or Cirrhosis.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e7bcbca e-flex e-con-boxed e-con e-parent\" data-id=\"e7bcbca\" 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-f7ef672 elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"f7ef672\" 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\/liverdisease.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-c9adad7 elementor-widget elementor-widget-heading\" data-id=\"c9adad7\" 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-5030039 elementor-widget elementor-widget-text-editor\" data-id=\"5030039\" 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\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#Variables\">variables&#8217;<\/a>\u00a0information:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d702e81 elementor-widget elementor-widget-heading\" data-id=\"d702e81\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Patient information<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4bb9972 elementor-widget elementor-widget-text-editor\" data-id=\"4bb9972\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"774\" data-end=\"950\">\n \t<li data-start=\"774\" data-end=\"862\" style=\"text-align: justify;\">\n<p data-start=\"776\" data-end=\"862\"><strong>age (-Age of the patient in ) &#8211;<\/strong> years. Normal ranges may vary depending on age.<\/p>\n<\/li>\n \t<li data-start=\"863\" data-end=\"950\" style=\"text-align: justify;\">\n<p data-start=\"865\" data-end=\"950\"><strong>sex (f or m) &#8211;<\/strong> Sex of the patient. Normal ranges for some blood tests differ by sex.<\/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-999ffeb elementor-widget elementor-widget-heading\" data-id=\"999ffeb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Blood test variables<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-360b29f elementor-widget elementor-widget-text-editor\" data-id=\"360b29f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"979\" data-end=\"2334\">\n \t<li data-start=\"979\" data-end=\"1085\" style=\"text-align: justify;\">\n<p data-start=\"981\" data-end=\"1085\"><strong>albumin (34-54 g\/L) &#8211;<\/strong> Low levels may indicate liver disease (Hepatitis, Cirrhosis) or kidney disease.<\/p>\n<\/li>\n \t<li data-start=\"1086\" data-end=\"1219\" style=\"text-align: justify;\">\n<p data-start=\"1088\" data-end=\"1219\"><strong>alkaline_phosphatase (40-129 U\/L) &#8211;<\/strong> Elevated levels may indicate liver damage, bile duct obstruction, or other liver conditions.<\/p>\n<\/li>\n \t<li data-start=\"1220\" data-end=\"1389\" style=\"text-align: justify;\">\n<p data-start=\"1222\" data-end=\"1389\"><strong>alanine aminotransferase (ALT, 7-55 U\/L) &#8211;<\/strong> Enzyme primarily found in the liver. High levels suggest liver injury from Hepatitis, Cirrhosis, or other liver diseases.<\/p>\n<\/li>\n \t<li data-start=\"1390\" data-end=\"1542\" style=\"text-align: justify;\">\n<p data-start=\"1392\" data-end=\"1542\"><strong style=\"background-color: transparent;\">aspartate aminotransferase (AST, 8-48 U\/L) &#8211;<\/strong><span style=\"background-color: transparent;\">\u00a0An enzyme present in the\u00a0<\/span>liver and muscles. Elevated AST can indicate liver disease, hepatitis, or cirrhosis.<\/p>\n<\/li>\n \t<li data-start=\"1543\" data-end=\"1682\" style=\"text-align: justify;\">\n<p data-start=\"1545\" data-end=\"1682\"><strong>bilirubin (1-12 mg\/L) &#8211;<\/strong> A yellow pigment formed from red blood cell breakdown. High levels indicate liver disease or bile obstruction.<\/p>\n<\/li>\n \t<li data-start=\"1683\" data-end=\"1802\" style=\"text-align: justify;\">\n<p data-start=\"1685\" data-end=\"1802\"><strong>cholinesterase (8-18 U\/L) &#8211;<\/strong> Enzyme synthesized by the liver. Low levels are associated with chronic liver disease.<\/p>\n<\/li>\n \t<li data-start=\"1803\" data-end=\"1909\" style=\"text-align: justify;\">\n<p data-start=\"1805\" data-end=\"1909\"><strong>cholesterol (&lt;5.2 mmol\/L) &#8211;<\/strong> Low or high levels can indicate liver dysfunction or metabolic disorders.<\/p>\n<\/li>\n \t<li data-start=\"1910\" data-end=\"2084\" style=\"text-align: justify;\">\n<p data-start=\"1912\" data-end=\"2084\"><strong>creatinine (M: 61.9-114.9<code data-start=\"1912\" data-end=\"1966\">\u00b5mol\/L<\/code>; F: 53-97.2 <code data-start=\"1912\" data-end=\"1966\">\u00b5mol\/L<\/code>) &#8211;<\/strong> Indicator of kidney function. Abnormal levels may indicate complications of liver disease that affect renal function.<\/p>\n<\/li>\n \t<li data-start=\"2085\" data-end=\"2233\" style=\"text-align: justify;\">\n<p data-start=\"2087\" data-end=\"2233\"><strong>gamma-glutamyl transferase (GGT, 0-30\/50 IU\/L) &#8211;<\/strong> Enzyme indicative of cholestasis and liver damage. Higher levels suggest greater liver injury.<\/p>\n<\/li>\n \t<li data-start=\"2234\" data-end=\"2334\" style=\"text-align: justify;\">\n<p data-start=\"2236\" data-end=\"2334\"><strong>protein (&lt;80mg) &#8211;<\/strong> Total protein level; abnormal levels may indicate liver or kidney dysfunction.<\/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-e571135 elementor-widget elementor-widget-heading\" data-id=\"e571135\" 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-d57188a elementor-widget elementor-widget-text-editor\" data-id=\"d57188a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<ul data-start=\"656\" data-end=\"746\">\n \t<li data-start=\"656\" data-end=\"746\" style=\"text-align: justify;\">\n<p data-start=\"658\" data-end=\"746\"><strong>diagnose<\/strong>: No disease, Suspect disease, Hepatitis C, Fibrosis, or Cirrhosis.<\/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-a13b2ab elementor-widget elementor-widget-text-editor\" data-id=\"a13b2ab\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3 style=\"font-family: Outfit, sans-serif; color: #242424;\">Instances<\/h3>\n<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-54d1e15 elementor-widget elementor-widget-text-editor\" data-id=\"54d1e15\" 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-3440003 elementor-widget elementor-widget-text-editor\" data-id=\"3440003\" 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 examine variable <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set#Distributions\">distributions<\/a>; the figure shows the number of patients with and without liver disease in the dataset.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ebc7c22 elementor-widget elementor-widget-image\" data-id=\"ebc7c22\" 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=\"595\" height=\"380\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/liver_disease-distribution-pie-chart.png\" class=\"attachment-large size-large wp-image-16383\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/liver_disease-distribution-pie-chart.png 595w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/liver_disease-distribution-pie-chart-300x192.png 300w\" sizes=\"(max-width: 595px) 100vw, 595px\" \/>\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-115d259 elementor-widget elementor-widget-text-editor\" data-id=\"115d259\" 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;\">As depicted in the image, 86.7% of patients show no liver disease, while 4.88% have cirrhosis, 3.41% have fibrosis, 3.9% have hepatitis, and 1.14% are suspected of having liver disease.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-18d0c04 elementor-widget elementor-widget-text-editor\" data-id=\"18d0c04\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<h3 style=\"font-family: Outfit, sans-serif; color: #242424;\">Input-target correlations<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b136317 elementor-widget elementor-widget-text-editor\" data-id=\"b136317\" 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>\u00a0indicate which clinical and demographic factors most influence the presence or absence of liver disease, 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-6d85686 elementor-widget elementor-widget-image\" data-id=\"6d85686\" 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=\"810\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/inputs-targets-correlations.webp\" class=\"attachment-large size-large wp-image-16381\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/inputs-targets-correlations.webp 600w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/08\/inputs-targets-correlations-222x300.webp 222w\" 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-0e9c51a elementor-widget elementor-widget-text-editor\" data-id=\"0e9c51a\" 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>aspartate aminotransferase<\/b>,\u00a0<b>gamma glutamyl transferase<\/b>, and\u00a0<b>alanine aminotransferase<\/b>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7036199 elementor-widget elementor-widget-heading\" data-id=\"7036199\" 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-4f29420 elementor-widget elementor-widget-text-editor\" data-id=\"4f29420\" 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 layer combines 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-73db5ca elementor-widget elementor-widget-image\" data-id=\"73db5ca\" 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=\"370\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Network-architecture-1.png\" class=\"attachment-large size-large wp-image-19666\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Network-architecture-1.png 973w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Network-architecture-1-300x139.png 300w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Network-architecture-1-768x355.png 768w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Network-architecture-1-600x277.png 600w\" 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-404f11e elementor-widget elementor-widget-text-editor\" data-id=\"404f11e\" 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 uses twelve diagnostic variables to produce five outputs (no disease, suspect disease, hepatitis, fibrosis, cirrhosis), 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-e991fe9 elementor-widget elementor-widget-heading\" data-id=\"e991fe9\" 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-1eebe9f elementor-widget elementor-widget-text-editor\" data-id=\"1eebe9f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"163\" data-end=\"435\" style=\"text-align: justify;\">Training a neural network uses a loss function and optimization algorithm to learn from data while avoiding overfitting, ensuring good performance on both training and new cases.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-55c17e2 elementor-widget elementor-widget-image\" data-id=\"55c17e2\" 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=\"800\" height=\"424\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Quasi-Newton-method-errors-history.png\" class=\"attachment-large size-large wp-image-19668\" alt=\"\" srcset=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Quasi-Newton-method-errors-history.png 980w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Quasi-Newton-method-errors-history-300x159.png 300w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Quasi-Newton-method-errors-history-768x408.png 768w, https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2025\/08\/Quasi-Newton-method-errors-history-600x318.png 600w\" 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-313abe0 elementor-widget elementor-widget-text-editor\" data-id=\"313abe0\" 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 to ensure accuracy and stability, with steadily decreasing training and selection errors (0.0553 and 0.0557 WSE), demonstrating effective learning and strong generalization.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ae54e46 elementor-widget elementor-widget-heading\" data-id=\"ae54e46\" 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\">5. Testing analysis<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-acdf340 elementor-widget elementor-widget-text-editor\" data-id=\"acdf340\" 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 the model is trained, 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-7f1a7cd elementor-widget elementor-widget-heading\" data-id=\"7f1a7cd\" 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-b57d6fb elementor-widget elementor-widget-text-editor\" data-id=\"b57d6fb\" 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 outcomes. It includes:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-100238a elementor-widget elementor-widget-text-editor\" data-id=\"100238a\" 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=\"187\" data-end=\"261\" style=\"text-align: justify;\">\n<p data-start=\"189\" data-end=\"261\"><strong data-start=\"189\" data-end=\"208\">True positives:<\/strong> patients correctly predicted to have liver disease<\/p>\n<\/li>\n \t<li data-start=\"262\" data-end=\"339\" style=\"text-align: justify;\">\n<p data-start=\"264\" data-end=\"339\"><strong data-start=\"264\" data-end=\"284\">False positives:<\/strong> patients incorrectly predicted to have liver disease<\/p>\n<\/li>\n \t<li data-start=\"340\" data-end=\"421\" style=\"text-align: justify;\">\n<p data-start=\"342\" data-end=\"421\"><strong data-start=\"342\" data-end=\"362\">False negatives:<\/strong> patients incorrectly predicted not to have liver disease<\/p>\n<\/li>\n \t<li data-start=\"422\" data-end=\"503\" style=\"text-align: justify;\">\n<p data-start=\"424\" data-end=\"503\"><strong data-start=\"424\" data-end=\"443\">True negatives:<\/strong> patients correctly predicted not to have liver disease<\/p>\n<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-aab7efd e-flex e-con-boxed e-con e-parent\" data-id=\"aab7efd\" 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-3a8f2fa elementor-widget elementor-widget-text-editor\" data-id=\"3a8f2fa\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<div class=\"tabla-responsive\">\n<table class=\"mi-tabla\">\n<tbody>\n<tr>\n<th><\/th>\n<th>Predicted no disease<\/th>\n<th>Predicted suspect disease<\/th>\n<th>Predicted hepatitis c<\/th>\n<th>Predicted fibrosis<\/th>\n<th>Predicted cirrhosis<\/th>\n<\/tr>\n<tr>\n<th style=\"text-align: left;\">Real no disease<\/th>\n<td style=\"text-align: right;\">107<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<\/tr>\n<tr>\n<th style=\"text-align: left;\">Real suspect disease<\/th>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<\/tr>\n<tr>\n<th style=\"text-align: left;\">Real hepatitis c<\/th>\n<td style=\"text-align: right;\">5<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<\/tr>\n<tr>\n<th style=\"text-align: left;\">Real fibrosis<\/th>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">2<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<\/tr>\n<tr>\n<th style=\"text-align: left;\">Real cirrhosis<\/th>\n<td style=\"text-align: right;\">1<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">0<\/td>\n<td style=\"text-align: right;\">2<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/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-faeae79 elementor-widget elementor-widget-text-editor\" data-id=\"faeae79\" 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;\">In this example, <strong>91.06%<\/strong> of cases were <strong>correctly classified<\/strong>\u00a0and\u00a0<strong>8.94%<\/strong> were <strong>misclassified<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-26e2485 elementor-widget elementor-widget-heading\" data-id=\"26e2485\" 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\">6. Model deployment<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5507d9 elementor-widget elementor-widget-text-editor\" data-id=\"f5507d9\" 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 confirming the neural network\u2019s ability to generalize, the model can be saved for future use in deployment mode.<\/p>\n\n<p style=\"text-align: justify;\">This allows the trained network to be applied to new patients, using their clinical variables to calculate the probability of liver disease.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-255928b elementor-widget elementor-widget-text-editor\" data-id=\"255928b\" 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;\">In deployment mode, healthcare professionals can use the model as a reliable diagnostic support tool for classifying new patients.<\/p>\n\n<p style=\"text-align: justify;\">The\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/my-account\/\">Neural Designer<\/a>\u00a0software exports the trained model automatically, making it easy to integrate into clinical practice.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b3bf8b0 e-flex e-con-boxed e-con e-parent\" data-id=\"b3bf8b0\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-f64c3ee e-con-full e-flex e-con e-child\" data-id=\"f64c3ee\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dc82923 elementor-widget__width-initial boton_descarga elementor-widget-mobile__width-initial elementor-widget elementor-widget-button\" data-id=\"dc82923\" 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<\/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-3a8fba4 elementor-widget elementor-widget-heading\" data-id=\"3a8fba4\" 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-83b1908 elementor-widget elementor-widget-text-editor\" data-id=\"83b1908\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"170\" data-end=\"394\" style=\"text-align: justify;\">The liver disease machine learning model, trained with the Medical University of Hannover dataset, performed highly in classifying patients as no disease, suspected disease, Hepatitis C, Fibrosis, or Cirrhosis.<\/p>\n<p data-start=\"396\" data-end=\"522\" style=\"text-align: justify;\">Key variables\u2014AST, GGT, and ALT\u2014are consistent with established clinical indicators, supporting the model\u2019s reliability.<\/p>\n<p data-start=\"524\" data-end=\"669\" style=\"text-align: justify;\">This tool can assist healthcare professionals in early detection, complementing clinical evaluations and improving diagnostic accuracy.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9fac07a elementor-widget elementor-widget-heading\" data-id=\"9fac07a\" 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-269020b elementor-widget elementor-widget-text-editor\" data-id=\"269020b\" 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;\">The data for this problem has been taken from the <a href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/HCV+data\">UCI Machine Learning Repository<\/a>.<\/li>\n \t<li style=\"text-align: justify;\">Lichtinghagen R et al. J Hepatol 2013; 59: 236-42.<\/li>\n \t<li style=\"text-align: justify;\">Hoffmann G et al. Using machine learning techniques to generate laboratory diagnostic pathways a case study. J Lab Precis Med 2018; 3: 58-67.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ea2b60b elementor-widget elementor-widget-heading\" data-id=\"ea2b60b\" 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":1980,"template":"","categories":[29],"tags":[38],"class_list":["post-3482","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 liver diseases using machine learning<\/title>\n<meta name=\"description\" content=\"Build a machine learning model to diagnose liver diseases 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