MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events
Researchers released MADE, a continuously updated benchmark for multi-label text classification in medical device adverse event reporting that addresses label imbalance and data contamination issues. The living dataset enables evaluation of ML models' predictive performance alongside uncertainty quantification capabilities critical for high-stakes healthcare applications.
MentionsMADE · multi-label text classification · medical device adverse events
Read full story at arXiv cs.CL →(arxiv.org)
Modelwire summarizes — we don’t republish. The full article lives on arxiv.org. If you’re a publisher and want a different summarization policy for your work, see our takedown page.