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Jason Alan Fries

As seen in: Nature
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Articles

Holistic evaluation of large language models for medical tasks with MedHELM - Nature Medicine

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By Suhana Bedi, Miguel Fuentes, Juan M. Banda, Timothy J. Keyes, Yifan Mai, Jason Alan Fries, Philip Chung, Fateme Nateghi Haredasht, Ivan Lopez, Ivan López, Iván López, Shivam Vedak, Sneha Jain, Ethan Goh, Robson Capasso, Jenelle Jindal, Faraz Ghoddusi, Albert S. Chiou, Michael Gensheimer, Hinesh Patel, Kevin A. Schulman, Kameron Collin Black, Harshita Sharma, Aditya Sharma, Yair Bannett, Roxana Daneshjou, Jonathan Chen, Nirmal Ravi, Nima Aghaeepour, Akshay S. Chaudhari, Thomas J. Wang, Sanmi Koyejo, Eric J Horvitz, Michael Pfeffer, Leonardo Schettini, Asad Aali, Nerissa Ambers
| Nature Verified
Abstract While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinical practice. Here we introduce MedHELM, an extensible evaluation framework with three contributions.
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How to interpret ‘zero-shot’ results from generative EHR models - Nature Medicine

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By Suhana Bedi, Jason Alan Fries, Nigam H. Shah
| Nature Verified
Generative models trained on electronic health records are viewed as ‘zero-shot predictors’ for clinical outcomes — but this interpretation is misleading.
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[1912.08041] The accuracy vs. coverage trade-off in patient-facing diagnosis models

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By Jason Alan, Jen Jen, Eric Kramer, Jason Alan Fries
| arxiv.org
Authors:Anitha Kannan, Jason Alan Fries, Eric Kramer, Jen Jen Chen, Nigam Shah, Xavier Amatriain (Submitted on 11 Dec 2019) Abstract: A third of adults in America use the Internet to diagnose medical concerns, and online symptom checkers are increasingly part of this process. These tools are powered by diagnosis models similar to clinical decision support systems, with the primary difference being the coverage of symptoms and diagnoses.
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