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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=\"monitoring\">\n<div class=\"nds-wrap\">\n<section class=\"nds-executive\"><h2>Inspect unusual patterns in one ECG recording<\/h2><p>A 140-input autoencoder models standardized heartbeats derived from PhysioNet record chf07 in the BIDMC Congestive Heart Failure Database. The current project contains 5,000 beats and reports anomaly ROC AUC 0.955.<\/p><div class=\"nds-kpis\"><div class=\"nds-kpi\"><strong>5,000<\/strong><span>Source records<\/span><\/div><div class=\"nds-kpi\"><strong>140<\/strong><span>Encoded input values<\/span><\/div><div class=\"nds-kpi\"><strong>3,355<\/strong><span>Testing-role records<\/span><\/div><div class=\"nds-kpi\"><strong>140<\/strong><span>Model outputs<\/span><\/div><\/div><div class=\"nds-actions\"><a class=\"aui aui-button\" href=\"#6-clinical-validation\">Review the current model<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-ecganomalydetection-licensed-20261006.zip\">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<section id=\"1-intended-use\" class=\"nds-card\"><h2>1. Clinical question and intended use<\/h2><p>This physiological-signal example studies reconstruction-error ranking against the supplied normal\/non-normal annotation. It is a recording-specific research benchmark, not a diagnostic or monitoring-alarm system.<\/p><div class=\"nds-value-grid\"><div class=\"nds-value-card\"><h3>Heartbeat representation<\/h3><p>Retain the same 140-point transformation.<\/p><\/div><div class=\"nds-value-card\"><h3>Error ranking<\/h3><p>Inspect the native anomaly ROC and reconstructions.<\/p><\/div><div class=\"nds-value-card\"><h3>Recording boundary<\/h3><p>Avoid treating a single recording as a clinical cohort.<\/p><\/div><\/div><div class=\"nds-audience\"><span>Biomedical signal analysis<\/span><span>Physiological research<\/span><span>Model validation<\/span><\/div><div class=\"nds-note nds-use-boundary\">Research use only. Unusual reconstruction error does not establish an arrhythmia or a clinical diagnosis.<\/div><\/section>\n<section id=\"2-cohort-endpoint\" class=\"nds-card\"><h2>2. Cohort, measurements and endpoint<\/h2><p>The first ECG channel of chf07 was decoded, segmented at annotation midpoints, interpolated to 140 values and standardized per beat. The final CSV column is 1 for normal and 0 for non-normal. The saved model assigns 1,234 rows to training, 411 to validation and 3,355 to testing. These roles differ from the separate 1,000-row OpenNN test_indices.csv file; results on this page use the .nd roles.<\/p><p>Source: <a href=\"https:\/\/physionet.org\/content\/chfdb\/1.0.0\/\">BIDMC Congestive Heart Failure Database, record chf07<\/a>. Dataset license: ODC-By-1.0. The downloadable ZIP includes the adapted data and attribution notices.<\/p><div class=\"nd-table-scroll\"><table><thead><tr><th scope=\"col\">Dataset measure<\/th><th scope=\"col\">Saved value<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Analysis unit<\/th><td>heartbeat segment<\/td><\/tr><tr><th scope=\"row\">Records<\/th><td>5,000<\/td><\/tr><tr><th scope=\"row\">Raw variables<\/th><td>141<\/td><\/tr><tr><th scope=\"row\">Encoded model inputs<\/th><td>140<\/td><\/tr><tr><th scope=\"row\">Model outputs<\/th><td>140<\/td><\/tr><tr><th scope=\"row\">Training roles<\/th><td>1234<\/td><\/tr><tr><th scope=\"row\">Validation \/ selection roles<\/th><td>411<\/td><\/tr><tr><th scope=\"row\">Testing roles<\/th><td>3355<\/td><\/tr><tr><th scope=\"row\">Unused roles<\/th><td>0<\/td><\/tr><\/tbody><\/table><\/div><details><summary>Inspect the complete saved variable schema<\/summary><div class=\"nd-table-scroll\"><table><thead><tr><th scope=\"col\">Field<\/th><th scope=\"col\">Role<\/th><th scope=\"col\">Type<\/th><th scope=\"col\">Categories<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">variable_1<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_2<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_3<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_4<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_5<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_6<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_7<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_8<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_9<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_10<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_11<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_12<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_13<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_14<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_15<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_16<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_17<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_18<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_19<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_20<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_21<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_22<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_23<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_24<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_25<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_26<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_27<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_28<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_29<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_30<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_31<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_32<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_33<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_34<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_35<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_36<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_37<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_38<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_39<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_40<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_41<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_42<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_43<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_44<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_45<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_46<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_47<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_48<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_49<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_50<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_51<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_52<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_53<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_54<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_55<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_56<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_57<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_58<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_59<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_60<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_61<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_62<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_63<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_64<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_65<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_66<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_67<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_68<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_69<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_70<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_71<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_72<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_73<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_74<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_75<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_76<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_77<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_78<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_79<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_80<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_81<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_82<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_83<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_84<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_85<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_86<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_87<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_88<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_89<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_90<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_91<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_92<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_93<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_94<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_95<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_96<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_97<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_98<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_99<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_100<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_101<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_102<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_103<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_104<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_105<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_106<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_107<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_108<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_109<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_110<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_111<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_112<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_113<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_114<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_115<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_116<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_117<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_118<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_119<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_120<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_121<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_122<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_123<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_124<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_125<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_126<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_127<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_128<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_129<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_130<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_131<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_132<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_133<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_134<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_135<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_136<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_137<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_138<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_139<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_140<\/th><td>InputTarget<\/td><td>Numeric<\/td><td><\/td><\/tr><tr><th scope=\"row\">variable_141<\/th><td>Evaluation<\/td><td>Binary<\/td><td>0, 1<\/td><\/tr><\/tbody><\/table><\/div><\/details><div class=\"nds-note nds-note--provenance\">The saved roles are retained exactly. Training and validation use the selected normal records, while testing includes both label types. These are record-level internal results; source recordings or acquisition windows can remain dependent.<\/div><\/section>\n<section id=\"3-model\" class=\"nds-card\"><h2>3. Model<\/h2><p>The model has 140 encoded inputs and 140 outputs. No architecture-selection experiment is recorded in this project. The diagram shows the topology used by the saved model.<\/p><div class=\"nd-table-scroll\"><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>140<\/td><td>140<\/td><td><\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>140<\/td><td>35<\/td><td>ReLU<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>35<\/td><td>17<\/td><td>ReLU<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>17<\/td><td>8<\/td><td>ReLU<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>8<\/td><td>17<\/td><td>ReLU<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>17<\/td><td>35<\/td><td>ReLU<\/td><\/tr><tr><th scope=\"row\">Dense<\/th><td>35<\/td><td>140<\/td><td>Identity<\/td><\/tr><tr><th scope=\"row\">Unscaling<\/th><td>140<\/td><td>140<\/td><td><\/td><\/tr><\/tbody><\/table><\/div><figure class=\"nds-architecture-figure\" data-model-stage=\"initial\"><a class=\"nds-architecture-link\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-licensed-ecganomalydetection-architecture-20261006.png\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" class=\"nds-architecture\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-licensed-ecganomalydetection-architecture-20261006.png\" alt=\"ECG anomaly detection with a heartbeat autoencoder \u2014 initial network architecture\"><\/a><figcaption>Topology of the saved current model; no architecture selection is recorded.<\/figcaption><\/figure><\/section>\n<section id=\"4-training\" class=\"nds-card\"><h2>4. Training strategy<\/h2><p>The saved training configuration uses Adam with MeanAbsoluteError.<\/p><h3>Adaptive moment estimation results<\/h3><div class=\"nd-table-scroll\"><table><thead><tr><th scope=\"col\">Measure<\/th><th scope=\"col\">Value<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Epochs number<\/th><td>100<\/td><\/tr><tr><th scope=\"row\">Elapsed time<\/th><td>00:00:02<\/td><\/tr><tr><th scope=\"row\">Stopping criterion<\/th><td>Maximum epochs number<\/td><\/tr><tr><th scope=\"row\">Training error<\/th><td>0.18<\/td><\/tr><tr><th scope=\"row\">Validation error<\/th><td>0.172<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nd-comparison-grid\"><div class=\"nd-comparison-item\"><figure class=\"nd-media-block\"><div class=\"nd-chart-bundle\" data-native-chart=\"nd-licensed-ecganomalydetection-t0-s2-20261006\"><div class=\"nd-chart-host\" id=\"nd-licensed-ecganomalydetection-t0-s2-20261006\" role=\"img\" aria-label=\"Adaptive moment estimation error history\"><\/div><img decoding=\"async\" class=\"nd-chart-fallback\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-licensed-ecganomalydetection-t0-s2-20261006.png\" alt=\"Adaptive moment estimation error history\"><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 error\",\"opacity\":1,\"showlegend\":true,\"type\":\"scatter\",\"x\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99],\"y\":[0.6520000100135803,0.5230000019073486,0.3799999952316284,0.32600000500679016,0.30000001192092896,0.28600001335144043,0.2800000011920929,0.2759999930858612,0.27300000190734863,0.26899999380111694,0.2669999897480011,0.2630000114440918,0.26100000739097595,0.257999986410141,0.25600001215934753,0.2529999911785126,0.25099998712539673,0.24899999797344208,0.24699999392032623,0.24500000476837158,0.24400000274181366,0.23999999463558197,0.23899999260902405,0.23600000143051147,0.23399999737739563,0.23199999332427979,0.23000000417232513,0.2280000001192093,0.22699999809265137,0.22499999403953552,0.2240000069141388,0.22300000488758087,0.22100000083446503,0.2199999988079071,0.21899999678134918,0.21799999475479126,0.21699999272823334,0.2160000056028366,0.21400000154972076,0.21400000154972076,0.21299999952316284,0.210999995470047,0.20999999344348907,0.20999999344348907,0.20900000631809235,0.2070000022649765,0.20600000023841858,0.20600000023841858,0.20499999821186066,0.20399999618530273,0.20200000703334808,0.20200000703334808,0.20000000298023224,0.20000000298023224,0.19900000095367432,0.1979999989271164,0.1979999989271164,0.19699999690055847,0.19599999487400055,0.19599999487400055,0.1940000057220459,0.19300000369548798,0.19300000369548798,0.19300000369548798,0.19200000166893005,0.19200000166893005,0.19099999964237213,0.1899999976158142,0.1899999976158142,0.1889999955892563,0.1889999955892563,0.18799999356269836,0.1889999955892563,0.18700000643730164,0.18700000643730164,0.18700000643730164,0.1860000044107437,0.1860000044107437,0.1850000023841858,0.1860000044107437,0.1850000023841858,0.1860000044107437,0.18400000035762787,0.18400000035762787,0.18400000035762787,0.18400000035762787,0.18299999833106995,0.18199999630451202,0.18199999630451202,0.18299999833106995,0.18199999630451202,0.18199999630451202,0.1809999942779541,0.18199999630451202,0.1809999942779541,0.18000000715255737,0.18000000715255737,0.18000000715255737,0.17900000512599945,0.18000000715255737]},{\"connectgaps\":false,\"line\":{\"color\":\"#ed982a\",\"dash\":\"solid\",\"width\":2},\"mode\":\"lines\",\"name\":\"Validation 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Native Neural Designer report for this project.<\/figcaption><\/figure><\/div><\/div><\/section>\n<section id=\"5-selection\" class=\"nds-card\"><h2>5. Model selection and baseline<\/h2><p>No model selection experiment is recorded for this version. The validation subset guides fitting where a training report is present; it is distinct from the held-out test rows.<\/p><\/section>\n<section id=\"6-clinical-validation\" class=\"nds-card\"><h2>6. Clinical validation<\/h2><p>The figures and tables below refer to the current project\u2019s saved testing analysis. The subset uses testing role 2; it contains 3355 source records.<\/p><p>ROC AUC describes ranking on this testing subset. Any optimal threshold shown in the saved ROC report was selected descriptively on that same subset; it is not an independently validated operating policy.<\/p><p>The report does not include a fixed-threshold confusion table. Sensitivity, specificity, precision and operating-point counts are therefore not claimed. The normal\/non-normal prevalence belongs to this selected recording, not a clinical population.<\/p><h3>Area under curve<\/h3><div class=\"nd-table-scroll\"><table><thead><tr><th scope=\"col\">Measure<\/th><th scope=\"col\">Value<\/th><\/tr><\/thead><tbody><tr><th scope=\"row\">Area under curve<\/th><td>0.955<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nd-comparison-grid\"><div class=\"nd-comparison-item\"><figure class=\"nd-media-block\"><div class=\"nd-chart-bundle\" data-native-chart=\"nd-licensed-ecganomalydetection-t1-s1-20261006\"><div class=\"nd-chart-host\" id=\"nd-licensed-ecganomalydetection-t1-s1-20261006\" role=\"img\" aria-label=\"Anomaly ROC chart\"><\/div><img decoding=\"async\" class=\"nd-chart-fallback\" src=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-licensed-ecganomalydetection-t1-s1-20261006.png\" alt=\"Anomaly ROC chart\"><script 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Native Neural Designer report for this project.<\/figcaption><\/figure><\/div><\/div><div class=\"nds-note\">Research use only. Unusual reconstruction error does not establish an arrhythmia or a clinical diagnosis.<\/div><\/section>\n<section id=\"7-workflow\" class=\"nds-card\"><h2>7. Workflow and reproducibility<\/h2><p>Open the downloaded project in Neural Designer, inspect the dataset roles and preprocessing, then review the saved task report. Use the same input schema and category order when calculating outputs. The ZIP contains the exact current .nd, its source data and the applicable dataset notices.<\/p><p>Research workflow: eligible record or image \u2192 measurement and schema checks \u2192 model score \u2192 expert review \u2192 confirmatory clinical method where appropriate. No model output should be used as an autonomous diagnosis or treatment instruction.<\/p><div class=\"nds-downloads\"><a class=\"aui aui-button\" href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-ecganomalydetection-licensed-20261006.zip\">Download model, data and licenses (ZIP)<\/a><a class=\"aui aui-button aui-button--secondary\" href=\"https:\/\/www.neuraldesigner.com\/downloads\/\">Download Neural Designer<\/a><\/div><\/section>\n<section id=\"8-safety\" class=\"nds-card\"><h2>8. Safety, generalizability and governance<\/h2><p>All beats come from one recording, so temporally correlated segments cannot establish patient-level transfer. No external validation, calibrated risk or clinical operating threshold is established. The supplied report contains ROC ranking and sample reconstructions but no confusion counts at a fixed operating threshold; clinician or signal-specialist review remains necessary.<\/p><div class=\"nds-note nds-note--warning\">Research use only. Unusual reconstruction error does not establish an arrhythmia or a clinical diagnosis.<\/div><\/section>\n<section id=\"references\" class=\"nds-card\"><h2>References<\/h2><ul><li><a href=\"https:\/\/physionet.org\/content\/chfdb\/1.0.0\/\">BIDMC Congestive Heart Failure Database, record chf07<\/a>. PhysioNet. 10.13026\/C29G60<\/li><li>Dataset terms: Open Data Commons Attribution License 1.0. Full attribution and transformations are included in <code>LICENSES\/DATASET-LICENSE.txt<\/code>.<\/li><li><a href=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2026\/10\/nd-ecganomalydetection-licensed-20261006.zip\">Current Neural Designer project and saved task report<\/a>, snapshot 6 October 2026.<\/li><\/ul><\/section>\n<\/div>\n<\/div>\n<style>\n.nd-chart-bundle{width:100%;max-width:760px;min-width:0;margin:24px auto;box-sizing:border-box;position:relative;overflow-x:auto;text-align:center;background:#fff;color:#30343b}\n.nd-chart-bundle .nd-chart-host{width:100%;height:440px;min-width:0;box-sizing:border-box}\n.nd-chart-bundle:not(.is-ready) .nd-chart-host{position:absolute;visibility:hidden}\n.nd-chart-bundle.is-ready .nd-chart-fallback{display:none!important}\n.nd-chart-bundle .nd-chart-fallback{display:block;margin:0 auto!important;width:100%;height:auto;max-width:100%}\n.nd-chart-bundle>script,.nd-chart-bundle>br,.nd-chart-bundle>p:empty{display:none!important}\n@media(max-width:600px){.nd-chart-bundle{margin:20px auto}.nd-chart-bundle .nd-chart-host{height:440px}}\n.nd-chart-bundle .nd-chart-host{min-width:0!important}.nd-chart-bundle{max-width:100%}html body .nd-comparison-grid>.nd-comparison-item:only-child{flex-basis:min(760px,100%)!important;width:min(760px,100%)!important}.ndb-card details,.nds-card details{margin:20px 0}.ndb-card summary,.nds-card summary{cursor:pointer;font-weight:600}<\/style><script data-noptimize=\"1\" data-cfasync=\"false\" src=\"https:\/\/cdn.plot.ly\/plotly-basic-4.0.0.min.js\"><\/script><script data-noptimize=\"1\">(()=>{const start=()=>{if(!window.Plotly)return;document.querySelectorAll('.nd-chart-bundle').forEach(bundle=>{if(bundle.dataset.started)return;bundle.dataset.started='1';const host=bundle.querySelector('.nd-chart-host'),source=bundle.querySelector('script[type=\"application\/json\"]');if(!host||!source)return;const figure=JSON.parse(source.textContent);window.Plotly.newPlot(host,figure.data,figure.layout,figure.config).then(async()=>{const title=host.querySelector('.gtitle');if(title)host.style.minWidth=Math.ceil(title.getComputedTextLength()+48)+'px';await window.Plotly.Plots.resize(host);bundle.classList.add('is-ready');if(window.ResizeObserver){let timer;new ResizeObserver(()=>{clearTimeout(timer);timer=setTimeout(()=>window.Plotly.Plots.resize(host),80);}).observe(bundle);}}).catch(error=>{bundle.dataset.error=String(error);console.error(error);});});};const ready=()=>{if(window.Plotly){start();return;}let count=0;const timer=setInterval(()=>{if(window.Plotly){clearInterval(timer);start();}else if(++count>200)clearInterval(timer);},50);};if(document.readyState==='loading')document.addEventListener('DOMContentLoaded',ready,{once:true});else ready();})();<\/script>","protected":false},"author":152,"featured_media":0,"template":"","categories":[29],"tags":[],"class_list":["post-23871","learning","type-learning","status-publish","hentry","category-examples"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>ECG anomaly detection with a heartbeat autoencoder - Neural Designer<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.neuraldesigner.com\/learning\/examples\/ecg-anomaly-detection\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ECG anomaly detection with a heartbeat autoencoder - Neural Designer\" \/>\n<meta property=\"og:description\" content=\"A 140-input autoencoder models standardized heartbeats derived from PhysioNet record chf07 in the BIDMC Congestive Heart Failure Database. 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