Key result
Optimized three-lead ECG detects myocardial infarction with ~85% sensitivity and ~11% false-positive rate.
Observational
Answers are grounded in this paper and cite their sources.
Demonstrates an optimized three-lead ECG decision-tree classifier for myocardial infarction in patient testing, indicating high diagnostic accuracy using simple manual measurements.
An optimized three-lead ECG hierarchial decision-tree type of classification system for myocardial infarction is presented. For selection of the best threshold values for each criterion and the best association of features, we developed a procedure based on "receiver operating characteristic" (ROC) curve data analysis and information theory. Optimization was obtained through maximization of information content of the criteria. The classifier is based on nine measurements that can be easily obtained by hand (QX duration, Q/R Y amplitude, R Y amplitude, Q/R Y duration, Q Z amplitude, QRS and T axes in the horizontal plane, Q Z duration and R Z amplitude) and achieved a satisfactory performance in an independent group of patients (true-positive ratio 0.853, false-positive ratio 0.105, average information content 0.308 bits).
No takes yet. Share an insight, caveat, or question.
Abreu‐Lima et al. (1983) conducted an observational in Myocardial infarction. Optimized three-lead ECG hierarchical decision-tree classification system was evaluated on Classification performance for myocardial infarction (true-positive ratio, false-positive ratio, and average information content). An optimized three-lead ECG classification system for myocardial infarction achieved a true-positive ratio of 0.853, false-positive ratio of 0.105, and 0.308 bits of information content.
Synapse has enriched 10 related papers. Consider them for comparative context: