Project 1: Using Large Language Models (LLMs) to Predict One-Year Hospitalization Rates in Kidney Transplant Recipients

Objective: This study aimed to find the most successful LLM prompt strategy for health outcome predictions and compare the functioning of various LLMs in clinical predictions.

Publication Details

Journal
George Mason University
Published
2024-09-01
DOI
https://doi.org/10.13021/mars/14509
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Project 1: Using Large Language Models (LLMs) to Predict One-Year Hospitalization Rates in Kidney Transplant Recipients

George Mason University
Machine Learning in Healthcare
article

Project 1: Using Large Language Models (LLMs) to Predict One-Year Hospitalization Rates in Kidney Transplant Recipients

article en

Abstract

Objective: This study aimed to find the most successful LLM prompt strategy for health outcome predictions and compare the functioning of various LLMs in clinical predictions.

George Mason University
Openalex Percentile: Top 67%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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Project 1: Using Large Language Models (LLMs) to Predict One-Year Hospitalization Rates in Kidney Transplant Recipients · George Mason University (2024) | TGRS Research Map | TGRS