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Evaluating the Role of Large Language Models Detection: A Comparative Analysis of Noninvasive Testing Methods and AI-Generated Diagnoses

Year: 2024

Type: article

Abstract: Nonalcoholic fatty liver disease (NAFLD) has become a global epidemic. The coexistence of NAFLD and type 2 diabetes mellitus (T2DM) is common, and their interaction significantly heightens the risk of adverse clinical outcomes. Despite advancements in medicine, diagnosing NAFLD remains a critical challenge. Large language models (LLMs) have shown exceptional capabilities in various medical applications. However, their potential in diagnosing NAFLD has yet to be fully explored.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.13805420

Authors: Yue Zhu, Ziwei Wang, Xiaoyi Zhang, Yuchen Zhang, Jiaqi Hong

Institutions: Georgia Institute of Technology, Chinese University of Hong Kong, Shenzhen, Albert Einstein College of Medicine, Jacobi Medical Center, China Academy of Art

Language: English

Topic: Liver Disease Diagnosis and Treatment

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W6911622972

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