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Assessment of Pathology Domain-Specific Knowledge of ChatGPT and Comparison to Human Performance
41
Zitationen
20
Autoren
2024
Jahr
Abstract
By demonstrating the ability of ChatGPT to answer pathology-specific questions at a level similar to (GPT-3.5) or exceeding (GPT-4) a trained pathologist, this study highlights the potential of large language models to be transformative in this space. In the future, more advanced iterations of these algorithms with increased domain-specific knowledge may have the potential to assist pathologists and enhance pathology resident training.
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Autoren
- Andrew Y. Wang
- Sherman Lin
- Christopher Tran
- Robert Homer
- Dan Wilsdon
- Joanna C. Walsh
- Emily A. Goebel
- Irene Sansano
- Snehal Sonawane
- Vincent Cockenpot
- Sanjay Mukhopadhyay
- Toros Taşkın
- Nusrat Zahra
- Luca Cima
- Orhan Semerci
- Birsen Gizem Özamrak
- Pallavi Mishra
- Naga Sarika Vennavalli
- Po-Hsuan Cameron Chen
- Matthew J. Cecchini
Institutionen
- Western University(CA)
- London Health Sciences Centre(CA)
- Yale University(US)
- Vall d'Hebron Hospital Universitari(ES)
- University of Illinois Chicago(US)
- Université Paris Sciences et Lettres(FR)
- Institut Curie(FR)
- Cleveland Clinic(US)
- Ağrı İbrahim Çeçen University(TR)
- Ospedale Santa Chiara(IT)
- Sağlık Bilimleri Üniversitesi(TR)
- Izmir University(TR)
- Lewisham and Greenwich NHS Trust(GB)
- Queen Elizabeth Hospital(GB)
- Yashoda Hospital(IN)