Enhancing the accuracy of GPT models in kidney stone diagnosis A comparison and optimization of GPT 3.5 and GPT 4.0

As artificial intelligence advances, Large Language Models (LLMs) have shown tremendous potential in medical diagnosis and treatment, yet existing research has not extensively explored their application in kidney stones.

Authors

Haoyang Zeng (ORCID: https://orcid.org/0000-0003-1057-2865)

Publication Details

Journal: Journal of Artificial Intelligence & Robotics
Published: 2025-07-25
DOI: https://doi.org/10.52768/3067-7947/1023
Primary Topic: Pancreatic and Hepatic Oncology Research
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Basic and Applied Basic Research Foundation of Guangdong Province

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article

Enhancing the accuracy of GPT models in kidney stone diagnosis A comparison and optimization of GPT 3.5 and GPT 4.0

Haoyang Zeng

Jul 25, 2025

Journal of Artificial Intelligence & Robotics

Pancreatic and Hepatic Oncology Research

article

Enhancing the accuracy of GPT models in kidney stone diagnosis A comparison and optimization of GPT 3.5 and GPT 4.0

Haoyang Zeng

July 25, 2025article en

Abstract

Journal of Artificial Intelligence & RoboticsVol. 2(2)

Basic and Applied Basic Research Foundation of Guangdong Province

Openalex Percentile: Top 61%

Pancreatic and Hepatic Oncology Research

DOI Open Access PDF OpenAlex

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Enhancing the accuracy of GPT models in kidney stone diagnosis A comparison and optimization of GPT 3.5 and GPT 4.0 — Haoyang Zeng · Journal of Artificial Intelligence & Robotics (2025) | TGRS Research Map | TGRS