AD-GPT: Large Language Models in Alzheimer's Disease

Ziyu Liu; Lintao Tang; Zeliang Sun; Zhengliang Liu; Yanjun Lyu; Wei Ruan; Yangshuang Xu; Liang Shan; Jiyoon Shin; Xiaohe Chen; Dajiang Zhu; Tianming Liu; Rongjie Liu; Chao Huang

arXiv · 2504.03071

AD-GPT: Large Language Models in Alzheimer's Disease

Ziyu Liu·Lintao Tang·Zeliang Sun·Zhengliang Liu·Yanjun Lyu·Wei Ruan·Yangshuang Xu·Liang Shan·Jiyoon Shin·Xiaohe Chen·Dajiang Zhu·Tianming Liu·Rongjie Liu·Chao Huang

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Abstract

Large language models (LLMs) have emerged as powerful tools for medical information retrieval, yet their accuracy and depth remain limited in specialized domains such as Alzheimer's disease (AD), a growing global health challenge. To address this gap, we introduce AD-GPT, a domain-specific generative pre-trained transformer designed to enhance the retrieval and analysis of AD-related genetic and neurobiological information. AD-GPT integrates diverse biomedical data sources, including potential AD-associated genes, molecular genetic information, and key gene variants linked to brain regions. We develop a stacked LLM architecture combining Llama3 and BERT, optimized for four critical tasks in AD research: (1) genetic information retrieval, (2) gene-brain region relationship assessment, (3) gene-AD relationship analysis, and (4) brain region-AD relationship mapping. Comparative evaluations against state-of-the-art LLMs demonstrate AD-GPT's superior precision and reliability across these tasks, underscoring its potential as a robust and specialized AI tool for advancing AD research and biomarker discovery.

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Ziyu Liu, Lintao Tang, Zeliang Sun, Zhengliang Liu, Yanjun Lyu, Wei Ruan, Yangshuang Xu, Liang Shan, Jiyoon Shin, Xiaohe Chen, Dajiang Zhu, Tianming Liu, Rongjie Liu, Chao Huang. 2025-04-03. AD-GPT: Large Language Models in Alzheimer's Disease. https://arxiv.org/abs/2504.03071

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