Supplementary Material to the Conference Paper "Towards Certifiable AI in Medicine: Illustrated for Multi-label ECG Classification Performance Metrics"

This repository contains supplementary material to the corresponding conference paper "Towards Certifiable AI in Medicine: Illustrated for Multi-label ECG Classification Performance Metrics", which was presented at the IEEE International Conference on Evolving and Adaptive Intelligent Systems 2024 in Madrid (EAIS24): https://ieeexplore.ieee.org/document/10570023 

The proposed resulting Quality Gate compilation for reliable performance evaluation is embedded within our generic and customizable AI lifecycle planning blueprint (MQG4AI) towards responsible AI, contributing to AI quality management. The resulting information management structure, envisioned as a standard for standards & use cases to be implemented as a tool for semi-automated, high-quality lifecycle design is outlined in more detail on GitHub (https://github.com/miriamelia/MQG4AI).