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Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores
14
Zitationen
32
Autoren
2023
Jahr
Abstract
In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.
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Autoren
- Hao Zhang
- Neil Jethani
- Simon Jones
- Nicholas Genes
- Vincent J. Major
- Ian Jaffe
- Anthony B. Cardillo
- Noah Heilenbach
- Nadia Fazal Ali
- Luke J. Bonanni
- Andrew J. Clayburn
- Zain Khera
- Erica C. Sadler
- Jaideep Prasad
- Jamie Schlacter
- Kevin Liu
- Benjamin A. Silva
- Sophie Montgomery
- Eric J. Kim
- Jacob Lester
- Theodore M. Hill
- Alba Avoricani
- Ethan Chervonski
- James Davydov
- William Small
- Eesha Chakravartty
- Himanshu Grover
- John A. Dodson
- Abraham A. Brody
- Yindalon Aphinyanaphongs
- Arjun V. Masurkar
- Narges Razavian