Large language models in medicine

AJ Thirunavukarasu, DSJ Ting, K Elangovan… - Nature medicine, 2023 - nature.com
Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …

Translation of AI into oncology clinical practice

I El Naqa, A Karolak, Y Luo, L Folio, AA Tarhini… - Oncogene, 2023 - nature.com
Artificial intelligence (AI) is a transformative technology that is capturing popular imagination
and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the …

[HTML][HTML] Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models

TH Kung, M Cheatham, A Medenilla, C Sillos… - PLoS digital …, 2023 - journals.plos.org
We evaluated the performance of a large language model called ChatGPT on the United
States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK …

Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial

G Wang, X Liu, Z Ying, G Yang, Z Chen, Z Liu… - Nature Medicine, 2023 - nature.com
The personalized titration and optimization of insulin regimens for treatment of type 2
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …

[HTML][HTML] Can ChatGPT provide intelligent diagnoses? A comparative study between predictive models and ChatGPT to define a new medical diagnostic bot

L Caruccio, S Cirillo, G Polese, G Solimando… - Expert Systems with …, 2024 - Elsevier
Intelligent diagnosis processes rely on Artificial Intelligence (AI) techniques to provide
possible diagnoses by analyzing patient data and medical information. To make accurate …

Ignore, trust, or negotiate: understanding clinician acceptance of AI-based treatment recommendations in health care

V Sivaraman, LA Bukowski, J Levin, JM Kahn… - Proceedings of the …, 2023 - dl.acm.org
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …

Steps to avoid overuse and misuse of machine learning in clinical research

V Volovici, NL Syn, A Ercole, JJ Zhao, N Liu - Nature Medicine, 2022 - nature.com
Steps to avoid overuse and misuse of machine learning in clinical research | Nature Medicine
Skip to main content Thank you for visiting nature.com. You are using a browser version with …

A future role for health applications of large language models depends on regulators enforcing safety standards

O Freyer, IC Wiest, JN Kather, S Gilbert - The Lancet Digital Health, 2024 - thelancet.com
Among the rapid integration of artificial intelligence in clinical settings, large language
models (LLMs), such as Generative Pre-trained Transformer-4, have emerged as …

[HTML][HTML] Guidelines for artificial intelligence in medicine: literature review and content analysis of frameworks

NL Crossnohere, M Elsaid, J Paskett… - Journal of Medical …, 2022 - jmir.org
Background: Artificial intelligence (AI) is rapidly expanding in medicine despite a lack of
consensus on its application and evaluation. Objective: We sought to identify current …

Methods for clinical evaluation of artificial intelligence algorithms for medical diagnosis

SH Park, K Han, HY Jang, JE Park, JG Lee, DW Kim… - Radiology, 2023 - pubs.rsna.org
Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in
practice is critical. Clinical evaluation aims to confirm acceptable AI performance through …