ZhiChao (David) Yang: MedicalBench Tests AI in Clinical Reasoning
ZhiChao (David) Yang, Senior Machine Learning Scientist at United Health Group, shared a post on LinkedIn:
”Imagine a doctor’s post-visit note about a patient mentions low hemoglobin, fatigue, and a blood transfusion.
It never says anemia.
Can your model still identify the condition and point to the evidence?
This type of implicit reasoning is common in real-world clinical documentation and remains a challenging problem for AI systems.
To support research in this area, Optum AI Science created MedicalBench, a dataset of expert-reviewed examples derived from MIMIC-IV
discharge summaries that evaluates evidence-grounded medical concept extraction.
Read the paper to learn why we created MedicalBench, see how current frontier models perform, and get access to the data.
Test your approach on our public leaderboard.
We’re looking forward to seeing what new models, architectures, and prompting strategies the research community develops.
Participation is subject to the terms of the user agreement and the Codabench terms of use.
This work wouldn’t have been possible without the incredible support of Beth Erickson, Gregory Lyng, Sanjit Singh Batra, Robert Tillman.”
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