Exploring the Impact of Large Language Models on Disease Diagnosis

The emergence of large language models (LLMs) has revolutionized various fields, including education, finance, marketing, healthcare, and medicine. In this review, we aim to explore the application of LLMs in the healthcare sector, with a specific focus on disease diagnostics. The review highlighted...

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Main Author: Ibrahim Almubark
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10833643/
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author Ibrahim Almubark
author_facet Ibrahim Almubark
author_sort Ibrahim Almubark
collection DOAJ
description The emergence of large language models (LLMs) has revolutionized various fields, including education, finance, marketing, healthcare, and medicine. In this review, we aim to explore the application of LLMs in the healthcare sector, with a specific focus on disease diagnostics. The review highlighted the widespread use of LLMs, such as GPT-4, ChatGPT, GPT-3.5, and LLaMA, with GPT-4 being the most frequently used in disease diagnostics due to its diverse applications, improved accuracy, and efficiency. This review shows that LLMs have utilized a variety of medical data sources, including general medical databases, specialized documents, medical images, and genomic data. Moreover, the focus of these LLMs spans a broad spectrum of healthcare fields, addressing chronic conditions, respiratory diseases, cancer, and rare diseases. The performance evaluation of LLMs involves both qualitative and quantitative measures assessing their diagnostic accuracy. The findings highlight the evolving nature of LLMs in improving diagnostic accuracy.
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spelling doaj-art-fd5be9bc24d245e3a7649d9d69e245d72025-01-21T00:01:21ZengIEEEIEEE Access2169-35362025-01-01138225823810.1109/ACCESS.2025.352702510833643Exploring the Impact of Large Language Models on Disease DiagnosisIbrahim Almubark0https://orcid.org/0009-0005-0735-501XDepartment of Information Technology, College of Computer, Qassim University, Buraydah, Saudi ArabiaThe emergence of large language models (LLMs) has revolutionized various fields, including education, finance, marketing, healthcare, and medicine. In this review, we aim to explore the application of LLMs in the healthcare sector, with a specific focus on disease diagnostics. The review highlighted the widespread use of LLMs, such as GPT-4, ChatGPT, GPT-3.5, and LLaMA, with GPT-4 being the most frequently used in disease diagnostics due to its diverse applications, improved accuracy, and efficiency. This review shows that LLMs have utilized a variety of medical data sources, including general medical databases, specialized documents, medical images, and genomic data. Moreover, the focus of these LLMs spans a broad spectrum of healthcare fields, addressing chronic conditions, respiratory diseases, cancer, and rare diseases. The performance evaluation of LLMs involves both qualitative and quantitative measures assessing their diagnostic accuracy. The findings highlight the evolving nature of LLMs in improving diagnostic accuracy.https://ieeexplore.ieee.org/document/10833643/Large language modelshealth care applicationsChatGPTGPT-4GPT-3.5BARD
spellingShingle Ibrahim Almubark
Exploring the Impact of Large Language Models on Disease Diagnosis
IEEE Access
Large language models
health care applications
ChatGPT
GPT-4
GPT-3.5
BARD
title Exploring the Impact of Large Language Models on Disease Diagnosis
title_full Exploring the Impact of Large Language Models on Disease Diagnosis
title_fullStr Exploring the Impact of Large Language Models on Disease Diagnosis
title_full_unstemmed Exploring the Impact of Large Language Models on Disease Diagnosis
title_short Exploring the Impact of Large Language Models on Disease Diagnosis
title_sort exploring the impact of large language models on disease diagnosis
topic Large language models
health care applications
ChatGPT
GPT-4
GPT-3.5
BARD
url https://ieeexplore.ieee.org/document/10833643/
work_keys_str_mv AT ibrahimalmubark exploringtheimpactoflargelanguagemodelsondiseasediagnosis