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background-size:cover!important;background-position:center!important; color:#193645; }\/* nd-shared-components:end *\/\n<\/style>\n<div class=\"nds\" data-health-profile=\"biomedical-research\">\n<div class=\"nds-wrap\">\n<section class=\"nds-executive\"><h2>Studying repeat blood donation from donation history<\/h2><p>Blood services can study donation history to plan outreach. This research example classifies whether a donor gave blood in the dataset&#x27;s recorded outcome period, using recency, frequency and time since the first donation.<\/p><div class=\"nds-kpis\"><div class=\"nds-kpi\"><strong>748<\/strong><span>Source records<\/span><\/div><div class=\"nds-kpi\"><strong>3<\/strong><span>Final input features<\/span><\/div><div class=\"nds-kpi\"><strong>149<\/strong><span>Test observations<\/span><\/div><div class=\"nds-kpi\"><strong>0.774<\/strong><span>Test ROC AUC<\/span><\/div><\/div><div class=\"nds-actions\"><a class=\"aui aui-button\" href=\"#6-clinical-validation\">Explore the model<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/blood-donors-targeting-data-20260921.csv\">Review the data<\/a><\/div><\/section>\n<ul class=\"nds-toc\"><li><a href=\"#1-intended-use\">Question and use<\/a><\/li><li><a href=\"#2-cohort-endpoint\">Cohort and endpoint<\/a><\/li><li><a href=\"#3-model\">Model<\/a><\/li><li><a href=\"#4-training\">Training<\/a><\/li><li><a href=\"#5-selection\">Selection<\/a><\/li><li><a href=\"#6-clinical-validation\">Validation<\/a><\/li><li><a href=\"#7-workflow\">Workflow<\/a><\/li><li><a href=\"#8-safety\">Safety and validity<\/a><\/li><\/ul>\n<span id=\"modeltype\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"1-intended-use\" class=\"nds-card\"><h2>1. Clinical question and intended use<\/h2><p>Blood services can study donation history when planning outreach. The endpoint here is a recorded return to donate in a particular month, so the model concerns participation rather than donor eligibility.<\/p><div class=\"nds-value-grid\"><div class=\"nds-value\"><h3>Donation history<\/h3><p>Use the three history variables retained by the final network.<\/p><\/div><div class=\"nds-value\"><h3>Return behaviour<\/h3><p>Compare model scores with donation in March 2007.<\/p><\/div><div class=\"nds-value\"><h3>Outreach research<\/h3><p>Evaluate contact policies separately from medical eligibility screening.<\/p><\/div><\/div><div class=\"nds-audience\"><span>Blood service planning<\/span><span>Public health research<\/span><span>Donor outreach<\/span><\/div><div class=\"nds-note nds-use-boundary\">Research and planning demonstration. It does not establish clinical validity, diagnosis, treatment or donor eligibility.<\/div><\/section>\n<span id=\"dataset\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"2-cohort-endpoint\" class=\"nds-card\"><h2>2. Cohort, measurements and endpoint<\/h2><p>The UCI Blood Transfusion Service Center dataset describes 748 donors from Hsin-Chu City, Taiwan. Its endpoint is donation in March 2007. The supplied model uses three history variables; it does not assess medical eligibility to donate.<\/p><p>The downloadable project, saved report and supplied source CSV define the exact version used here. Repository: <a href=\"https:\/\/archive.ics.uci.edu\/dataset\/176\/blood+transfusion+service+center\">original dataset\/source record<\/a>. <\/p><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Subset<\/th><th scope=\"col\">Records<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Training<\/th><td>450<\/td><\/tr><tr><th scope=\"row\">Validation \/ selection<\/th><td>149<\/td><\/tr><tr><th scope=\"row\">Testing<\/th><td>149<\/td><\/tr><tr><th scope=\"row\">Unused<\/th><td>0<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Variable<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Type<\/th><th scope=\"col\">Encoding<\/th><th scope=\"col\">Unit<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">recency<\/th><td>Input<\/td><td>Numeric<\/td><td><\/td><td>months<\/td><\/tr><tr><th scope=\"row\">frequency<\/th><td>Input<\/td><td>Numeric<\/td><td><\/td><td>donations<\/td><\/tr><tr><th scope=\"row\">time<\/th><td>Input<\/td><td>Numeric<\/td><td><\/td><td>months<\/td><\/tr><tr><th scope=\"row\">donation<\/th><td>Target<\/td><td>Binary<\/td><td>no; yes<\/td><td>As supplied<\/td><\/tr><\/tbody><\/table><\/div><figure class=\"nd-native-figure\"><div class=\"nd-chart-bundle\" tabindex=\"0\" role=\"group\" aria-label=\"Interactive chart; scroll horizontally on narrow screens\" data-native-chart=\"nd-blood-donors-targeting-t0-s4-20260921\"><div class=\"nd-chart-host\" id=\"nd-blood-donors-targeting-t0-s4-20260921\" role=\"img\" aria-label=\"donation pie chart\"><\/div><p class=\"nd-chart-fallback\">Interactive chart: donation pie chart. Enable JavaScript to explore it.<\/p><script type=\"application\/json\">{\"config\":{\"displayModeBar\":true,\"displaylogo\":false,\"editable\":false,\"responsive\":true,\"scrollZoom\":true,\"toImageButtonOptions\":{\"filename\":\"neural-designer-chart\",\"format\":\"svg\"}},\"data\":[{\"direction\":\"clockwise\",\"hovertemplate\":\"%{label}\\u003cbr\\u003e%{value}\\u003cbr\\u003e%{percent}\\u003cextra\\u003e\\u003c\/extra\\u003e\",\"labels\":[\"no\",\"yes\"],\"marker\":{\"colors\":[\"#209fdf\",\"#092d40\"]},\"showlegend\":true,\"sort\":false,\"textinfo\":\"label+percent\",\"type\":\"pie\",\"values\":[76.19999694824219,23.799999237060547]}],\"layout\":{\"autosize\":true,\"font\":{\"color\":\"#30343b\",\"family\":\"Arial, sans-serif\",\"size\":14},\"hovermode\":\"closest\",\"legend\":{},\"margin\":{\"b\":68,\"l\":72,\"pad\":4,\"r\":36,\"t\":112},\"paper_bgcolor\":\"#ffffff\",\"plot_bgcolor\":\"#ffffff\",\"title\":{\"automargin\":true,\"pad\":{\"t\":48},\"text\":\"donation pie chart\",\"x\":0.5,\"xanchor\":\"center\",\"y\":1,\"yanchor\":\"top\",\"yref\":\"container\"}}}<\/script><\/div><figcaption>donation pie chart. Exported with Neural Designer from the saved task report.<\/figcaption><\/figure><figure class=\"nd-native-figure\"><div class=\"nd-chart-bundle\" tabindex=\"0\" role=\"group\" aria-label=\"Interactive chart; scroll horizontally on narrow screens\" data-native-chart=\"nd-blood-donors-targeting-t1-s1-20260921\"><div class=\"nd-chart-host\" id=\"nd-blood-donors-targeting-t1-s1-20260921\" role=\"img\" aria-label=\"donation Pearson correlations chart\"><\/div><p class=\"nd-chart-fallback\">Interactive chart: donation Pearson correlations chart. Enable JavaScript to explore it.<\/p><script type=\"application\/json\">{\"config\":{\"displayModeBar\":true,\"displaylogo\":false,\"editable\":false,\"responsive\":true,\"scrollZoom\":true,\"toImageButtonOptions\":{\"filename\":\"neural-designer-chart\",\"format\":\"svg\"}},\"data\":[{\"marker\":{\"color\":\"#209fdf\"},\"name\":\"\",\"opacity\":1,\"orientation\":\"h\",\"showlegend\":false,\"type\":\"bar\",\"x\":[-0.3100000023841858,-0.0357000008225441,0.21199999749660492],\"y\":[\"recency\",\"time\",\"frequency\"]}],\"layout\":{\"autosize\":true,\"font\":{\"color\":\"#30343b\",\"family\":\"Arial, sans-serif\",\"size\":14},\"hovermode\":\"closest\",\"margin\":{\"b\":68,\"l\":72,\"pad\":4,\"r\":36,\"t\":112},\"paper_bgcolor\":\"#ffffff\",\"plot_bgcolor\":\"#ffffff\",\"title\":{\"automargin\":true,\"pad\":{\"t\":48},\"text\":\"donation Pearson correlations chart\",\"x\":0.5,\"xanchor\":\"center\",\"y\":1,\"yanchor\":\"top\",\"yref\":\"container\"},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"range\":[-1,1],\"title\":{\"text\":\"Correlation\"},\"zerolinecolor\":\"#aeb6c2\"},\"yaxis\":{\"automargin\":true,\"autorange\":\"reversed\",\"categoryarray\":[\"recency\",\"time\",\"frequency\"],\"categoryorder\":\"array\",\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"type\":\"category\",\"zerolinecolor\":\"#aeb6c2\"}}}<\/script><\/div><figcaption>donation Pearson correlations chart. Exported with Neural Designer from the saved task report.<\/figcaption><\/figure><div class=\"nds-note nds-note--provenance\">The downloadable project, saved report and supplied source CSV define the exact version used here. Repository: <a href=\"https:\/\/archive.ics.uci.edu\/dataset\/176\/blood+transfusion+service+center\">original dataset\/source record<\/a>. This is internal validation using the saved record-level split. Grouped or temporal independence has not been established.<\/div><\/section>\n<span id=\"neural_network\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"3-model\" class=\"nds-card\"><h2>3. Model<\/h2><p>The final model has <strong>3 encoded input features<\/strong> and <strong>1 outputs<\/strong>. The following dimensions describe the final saved network.<\/p><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Layer<\/th><th scope=\"col\">Input shape<\/th><th scope=\"col\">Output shape<\/th><th scope=\"col\">Activation<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Scaling<\/th><td>3<\/td><td>3<\/td><td>\u2014<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>3<\/td><td>3<\/td><td>Tanh<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>3<\/td><td>1<\/td><td>Sigmoid<\/td><\/tr><\/tbody><\/table><\/div><p>Output semantics: the sigmoid score increases toward <strong>yes<\/strong>; no is the other class. Calibration has not been evaluated, so scores are not presented as calibrated probabilities.<\/p><figure class=\"nds-architecture-figure\" data-model-stage=\"initial\"><a href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/nd-blood-donors-targeting-final-architecture-20260921.png\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" class=\"nds-architecture\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/nd-blood-donors-targeting-final-architecture-20260921.png\" alt=\"Studying repeat blood donation from donation history: initial Neural Designer architecture\"><\/a><figcaption>Architecture used for this model; no architecture-selection experiment is recorded. Diagram labels show original variables; categorical expansion and the numeric layer dimensions are documented in the model table.<\/figcaption><\/figure><\/section>\n<span id=\"training_strategy\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"4-training\" class=\"nds-card\"><h2>4. Training strategy<\/h2><p>The saved training configuration uses WeightedSquaredError with QuasiNewton. Training minimizes the recorded objective; the validation subset monitors generalization during fitting. The testing subset is used for the evaluation below.<\/p><figure class=\"nd-native-figure\"><div class=\"nd-chart-bundle\" tabindex=\"0\" role=\"group\" aria-label=\"Interactive chart; scroll horizontally on narrow screens\" data-native-chart=\"nd-blood-donors-targeting-t2-s2-20260921\"><div class=\"nd-chart-host\" id=\"nd-blood-donors-targeting-t2-s2-20260921\" role=\"img\" aria-label=\"Quasi-Newton method error history\"><\/div><p class=\"nd-chart-fallback\">Interactive chart: Quasi-Newton method error history. Enable JavaScript to explore it.<\/p><script type=\"application\/json\">{\"config\":{\"displayModeBar\":true,\"displaylogo\":false,\"editable\":false,\"responsive\":true,\"scrollZoom\":true,\"toImageButtonOptions\":{\"filename\":\"neural-designer-chart\",\"format\":\"svg\"}},\"data\":[{\"connectgaps\":false,\"line\":{\"color\":\"#529cc2\",\"dash\":\"solid\",\"width\":2},\"mode\":\"lines\",\"name\":\"Training 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sans-serif\",\"size\":14},\"hovermode\":\"closest\",\"legend\":{\"orientation\":\"h\",\"x\":0.5,\"xanchor\":\"center\",\"y\":-0.24,\"yanchor\":\"top\"},\"margin\":{\"b\":120,\"l\":72,\"pad\":4,\"r\":36,\"t\":112},\"paper_bgcolor\":\"#ffffff\",\"plot_bgcolor\":\"#ffffff\",\"title\":{\"automargin\":true,\"pad\":{\"t\":48},\"text\":\"Quasi-Newton method error history\",\"x\":0.5,\"xanchor\":\"center\",\"y\":1,\"yanchor\":\"top\",\"yref\":\"container\"},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"range\":[0,117],\"title\":{\"text\":\"Epoch\"},\"zerolinecolor\":\"#aeb6c2\"},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"range\":[0,1.0002],\"title\":{\"text\":\"Weighted squared error\"},\"zerolinecolor\":\"#aeb6c2\"}}}<\/script><\/div><figcaption>Quasi-Newton method error history. Exported with Neural Designer from the saved task report.<\/figcaption><\/figure><h3>Quasi-Newton method results<\/h3><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Measure<\/th><th scope=\"col\">Value<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Epochs number<\/th><td>118<\/td><\/tr><tr><th scope=\"row\">Elapsed time<\/th><td>00:00:00<\/td><\/tr><tr><th scope=\"row\">Stopping criterion<\/th><td>Maximum validation error increases<\/td><\/tr><tr><th scope=\"row\">Training error<\/th><td>0.638<\/td><\/tr><tr><th scope=\"row\">Validation error<\/th><td>0.629<\/td><\/tr><\/tbody><\/table><\/div><\/section>\n<section id=\"5-selection\" class=\"nds-card\"><h2>5. Model selection and baseline<\/h2><p>No model selection experiment is recorded in this supplied project. The displayed architecture is the trained model used for testing; earlier article claims about a different selected architecture do not apply to this version.<\/p><p>A transparent test-set comparator is the majority-class rule, with accuracy 76.5%. This is a baseline for interpretation, not an alternative model fitted on the test labels.<\/p><\/section>\n<span id=\"testing_analysis\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"6-clinical-validation\" class=\"nds-card\"><h2>6. Clinical validation<\/h2><p>The final classifier is evaluated on <strong>149 testing records<\/strong>. The confusion counts below were reproduced from the saved model. Rows are actual classes and columns are predicted classes. The decision threshold is 0.5 on the score for yes.<\/p><p>Test class prevalence is shown by the support counts. Accuracy is 71.8% and macro F1 is 0.677. ROC AUC is 0.774. The native ROC optimal threshold is descriptive of this test set and is not an independently validated operating policy.<\/p><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Actual \/ predicted<\/th><th scope=\"col\">no<\/th><th scope=\"col\">yes<\/th><th scope=\"col\">Total<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">no<\/th><td>80<\/td><td>34<\/td><td>114<\/td><\/tr><tr><th scope=\"row\">yes<\/th><td>8<\/td><td>27<\/td><td>35<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nd-table-scroll\" tabindex=\"0\"><table><thead><tr><th scope=\"col\">Class<\/th><th scope=\"col\">Test cases<\/th><th scope=\"col\">Sensitivity \/ recall<\/th><th scope=\"col\">Specificity<\/th><th scope=\"col\">Precision \/ PPV<\/th><th scope=\"col\">F1<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">no<\/th><td>114<\/td><td>70.2%<\/td><td>77.1%<\/td><td>90.9%<\/td><td>0.792<\/td><\/tr><tr><th scope=\"row\">yes<\/th><td>35<\/td><td>77.1%<\/td><td>70.2%<\/td><td>44.3%<\/td><td>0.562<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nd-native-test-figures\"><figure class=\"nd-native-figure\"><div class=\"nd-chart-bundle\" tabindex=\"0\" role=\"group\" aria-label=\"Interactive chart; scroll horizontally on narrow screens\" data-native-chart=\"nd-blood-donors-targeting-t3-s1-20260921\"><div class=\"nd-chart-host\" id=\"nd-blood-donors-targeting-t3-s1-20260921\" role=\"img\" aria-label=\"ROC chart\"><\/div><p class=\"nd-chart-fallback\">Interactive chart: ROC chart. Enable JavaScript to explore it.<\/p><script type=\"application\/json\">{\"config\":{\"displayModeBar\":true,\"displaylogo\":false,\"editable\":false,\"responsive\":true,\"scrollZoom\":true,\"toImageButtonOptions\":{\"filename\":\"neural-designer-chart\",\"format\":\"svg\"}},\"data\":[{\"connectgaps\":false,\"fill\":\"tozeroy\",\"fillcolor\":\"rgba(82,156,194,0.300)\",\"line\":{\"color\":\"#ffffff\",\"dash\":\"solid\",\"width\":1},\"marker\":{\"color\":\"#529cc2\",\"size\":5,\"symbol\":\"circle\"},\"mode\":\"lines+markers\",\"name\":\"Random 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Positive Rate (sensitivity)\",\"opacity\":1,\"showlegend\":false,\"type\":\"scatter\",\"x\":[0,1],\"y\":[0,1]},{\"connectgaps\":false,\"marker\":{\"color\":\"#ed982a\",\"size\":8,\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"True Positive Rate (sensitivity)\",\"opacity\":1,\"showlegend\":false,\"type\":\"scatter\",\"x\":[0.21929800510406494],\"y\":[0.7428569793701172]}],\"layout\":{\"annotations\":[{\"font\":{\"color\":\"#404044\"},\"showarrow\":false,\"text\":\"Optimal Threshold\",\"x\":0.389298005104065,\"y\":0.6528569793701172},{\"font\":{\"color\":\"#404044\"},\"showarrow\":false,\"text\":\"Area under curve: 0.774\",\"x\":0.7,\"y\":0.02}],\"autosize\":true,\"font\":{\"color\":\"#30343b\",\"family\":\"Arial, sans-serif\",\"size\":14},\"hovermode\":\"closest\",\"margin\":{\"b\":68,\"l\":72,\"pad\":4,\"r\":36,\"t\":112},\"paper_bgcolor\":\"#ffffff\",\"plot_bgcolor\":\"#ffffff\",\"title\":{\"automargin\":true,\"pad\":{\"t\":48},\"text\":\"ROC chart\",\"x\":0.5,\"xanchor\":\"center\",\"y\":1,\"yanchor\":\"top\",\"yref\":\"container\"},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"range\":[0,1],\"title\":{\"text\":\"False Positive Rate (1-specificity)\"},\"zerolinecolor\":\"#aeb6c2\"},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"#d9dde3\",\"linecolor\":\"#9aa3ad\",\"range\":[0,1],\"title\":{\"text\":\"True Positive Rate (sensitivity)\"},\"zerolinecolor\":\"#aeb6c2\"}}}<\/script><\/div><figcaption>ROC chart. Exported with Neural Designer from the saved task report.<\/figcaption><\/figure><\/div><div class=\"nds-note\">This is internal record-level evidence. Discrimination does not establish calibration, clinical utility or benefit to patients.<\/div><\/section>\n<span id=\"model_deployment\" class=\"nd-legacy-anchor\" aria-hidden=\"true\"><\/span><section id=\"7-workflow\" class=\"nds-card\"><h2>7. Workflow and reproducibility<\/h2><p>Validated inputs \u2192 saved preprocessing \u2192 neural network \u2192 score or estimate \u2192 domain review. The ZIP contains the original project, source CSV, schema, test metrics and standalone interactive chart exports. The project hash in the schema identifies this exact version.<\/p><div class=\"nd-model-calculator\" id=\"nd-model-blood-donors-targeting\"><h3>Explore the exported model<\/h3><p>This research demonstration runs locally in your browser. Values outside the training range are outside the validated domain and are rejected. A valid input range does not guarantee that a combination is physically or operationally plausible.<\/p><p>This is not a diagnosis and must not guide medical treatment or donor eligibility.<\/p><div class=\"nd-model-fields\"><\/div><div class=\"nd-model-actions\"><button class=\"aui aui-button nd-model-calculate\" type=\"button\">Calculate<\/button><button class=\"aui aui-button aui-button--secondary nd-model-reset\" type=\"button\">Reset example<\/button><\/div><div class=\"nd-model-result\" role=\"status\" aria-live=\"polite\"><\/div><\/div><script data-noptimize=\"1\">(()=>{function Identity(x) {\n\treturn x;\n}\nfunction Sigmoid(x) {\n\tvar z = 1\/(1+Math.exp(-x));\n\treturn z;\n}\nfunction Tanh(x) {\n\treturn Math.tanh(x);\n}\nfunction calculate_outputs(inputs)\n{\n\tvar recency = +inputs[0];\n\tvar frequency = +inputs[1];\n\tvar time = +inputs[2];\n\n\tvar scaled_recency = recency*0.1236093938-1.17511487;\n\tvar scaled_frequency = frequency*0.1713675559-0.9450423717;\n\tvar scaled_time = time*0.04105022922-1.407288074;\n\tvar dense_layer_1_output_0 = Tanh( 0.2556088865 + (-0.1241200194*scaled_recency) + (0.4992599487*scaled_frequency) + (-0.07227318734*scaled_time) );\n\tvar dense_layer_1_output_1 = Tanh( -0.5221639872 + (-0.4831526577*scaled_recency) + (0.5977103114*scaled_frequency) + (-0.4601962864*scaled_time) );\n\tvar dense_layer_1_output_2 = Tanh( 0.05770132691 + (1.496287704*scaled_recency) + (-1.269449115*scaled_frequency) + (0.0777040273*scaled_time) );\n\tvar donation = Sigmoid( 0.4039789438 + (0.1207531765*dense_layer_1_output_0) + (1.8358078*dense_layer_1_output_1) + (0.02088464983*dense_layer_1_output_2) );\n\tvar out = [];\n\tout.push(donation);\n\n\treturn out;\n}\nconst cfg={\"fields\":[{\"name\":\"recency\",\"n\":1,\"type\":\"Numeric\",\"categories\":[],\"min\":0.0,\"max\":74.0,\"value\":5.0,\"unit\":\"months\"},{\"name\":\"frequency\",\"n\":1,\"type\":\"Numeric\",\"categories\":[],\"min\":1.0,\"max\":50.0,\"value\":46.0,\"unit\":\"donations\"},{\"name\":\"time\",\"n\":1,\"type\":\"Numeric\",\"categories\":[],\"min\":2.0,\"max\":98.0,\"value\":98.0,\"unit\":\"months\"}],\"output_names\":[\"yes score\"],\"reference\":[0.9107346482493182]},root=document.getElementById(\"nd-model-blood-donors-targeting\");if(!root)return;const grid=root.querySelector(\".nd-model-fields\"),result=root.querySelector(\".nd-model-result\"),controls=[];cfg.fields.forEach((f,i)=>{const wrap=document.createElement(\"div\");wrap.className=\"nd-model-field\";const label=document.createElement(\"label\"),id=root.id+\"-\"+i;label.htmlFor=id;label.textContent=f.name.replaceAll(\"_\",\" \")+(f.unit?\" (\"+f.unit+\")\":\"\");let input;if(f.categories?.length){input=document.createElement(\"select\");f.categories.forEach((name,k)=>{const option=document.createElement(\"option\");option.value=String(k);option.textContent=name;input.appendChild(option);});}else{input=document.createElement(\"input\");input.type=\"number\";input.step=\"any\";input.min=String(f.min);input.max=String(f.max);}input.id=id;input.value=String(f.value);wrap.append(label,input);grid.appendChild(wrap);controls.push(input);});const calculate=()=>{const inputs=[];let valid=true;cfg.fields.forEach((f,i)=>{const el=controls[i],v=Number(el.value);let bad=el.value.trim()===\"\"||!Number.isFinite(v);if(!f.categories?.length)bad=bad||v<f.min||v>f.max;el.setAttribute(\"aria-invalid\",bad?\"true\":\"false\");if(bad)valid=false;if(f.n>1){for(let k=0;k<f.n;k++)inputs.push(k===v?1:0);}else inputs.push(v);});if(!valid){result.textContent=\"Enter a valid value within every displayed input range.\";return;}let outputs=calculate_outputs(inputs);if(outputs.some(v=>!Number.isFinite(v))){result.textContent=\"The model could not evaluate these inputs.\";return;}result.textContent=outputs.map((v,i)=>cfg.output_names[i]+\": \"+Number(v.toPrecision(7))).join(\"\\n\");root.dataset.outputs=JSON.stringify(outputs);};root.querySelector(\".nd-model-calculate\").addEventListener(\"click\",calculate);root.querySelector(\".nd-model-reset\").addEventListener(\"click\",()=>{controls.forEach((el,i)=>el.value=String(cfg.fields[i].value));calculate();});calculate();})();<\/script><div class=\"nds-downloads\"><a class=\"aui aui-button\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/blood-donors-targeting-neural-designer-20260921.zip\">Download project and exports (ZIP)<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/blood-donors-targeting-data-20260921.csv\">Download source data (CSV)<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/blood-donors-targeting-schema-20260921.zip\">Download input schema (ZIP)<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/downloads\/\">Reproduce with Neural Designer<\/a><\/div><\/section>\n<section id=\"8-safety\" class=\"nds-card\"><h2>8. Safety, generalizability and governance<\/h2><p>The cohort represents one historical service, not current donors across regions. Validate on later donor cohorts and assess outreach effects separately. Eligibility, consent and contact policies require expert review. There is no external validation or evidence of a clinical benefit from this score.<\/p><p>No external validation or independent calibration study is included. Preprocessing statistics and model choices should be refitted within a prospective or grouped validation design. Correlations and directional responses describe associations, not causes. Human review is required before an operational decision.<\/p><p>Confidence intervals, subgroup performance, calibration curves and decision-cost validation are not established by these tasks. Predictive values apply to the observed test class distribution and may change when prevalence shifts.<\/p><div class=\"nds-note nds-note--warning\">Expert review and separate external validation are required before any medical use.<\/div><\/section>\n<section id=\"references\" class=\"nds-card\"><h2>References<\/h2><ul><li><a href=\"https:\/\/archive.ics.uci.edu\/dataset\/176\/blood+transfusion+service+center\">Dataset source and provenance<\/a>.<\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/09\/blood-donors-targeting-neural-designer-20260921.zip\">Neural Designer project and saved task evidence, 21 September 2026<\/a>.<\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\/\">Neural Designer testing-analysis documentation<\/a>.<\/li><\/ul><\/section>\n<\/div>\n<\/div>\n<script data-noptimize=\"1\" data-cfasync=\"false\" src=\"https:\/\/cdn.plot.ly\/plotly-basic-4.0.0.min.js\"><\/script><script 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