Studying mortality after heart failure

Version: 2026-09-21

The prepared Heart Failure Clinical Records table contains 299 patient records, with 96 recorded deaths and 203 records without a death event. The endpoint is DEATH_EVENT: 1 means death observed during follow-up; 0 means no death observed during that period. The prepared CSV has 11 predictors and excludes the original follow-up-time column. Follow-up duration varies in the source cohort, so this binary endpoint is not a common fixed-horizon mortality outcome.

The 59-record test subset is small and comes from the same historical cohort as the training records. This binary classifier does not model event time or censoring and cannot provide a validated 30-day or one-year mortality risk. Before any medical use, establish predictor availability at the assessment time, refit preprocessing within training, evaluate on an independent cohort and obtain clinician review.

Open the .nd project in Neural Designer. Its embedded data, parameters, saved sample roles and task report are preserved. If the original CSV path is unavailable, select the CSV included here. The source CSV may include unused columns; the embedded project defines the exact modelling schema.

The charts/ directory contains standalone HTML exported with the application chart builder. The schema and test-metrics files identify the exact inputs, outputs, evidence and source hash.

Dataset source: https://archive.ics.uci.edu/dataset/519/heart+failure+clinical+records
Retain the source attribution and its applicable dataset terms.

The original HTML expression is included unchanged. native-model.js contains the same mathematical functions extracted from it.
