mlsanityData to 7 Oct 2026

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

arXiv 2504.03071 ↗First posted 3 Apr 2025cs.CL cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 19 of its 58 references that are in the map. First posted on arXiv 3 Apr 2025.

Builds on

19 of 58 references.

References · 19

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  4. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  5. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,175
  6. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
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  8. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  9. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 996
  10. 2022BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Miningcited by 531
  11. 2023Ragas: Automated Evaluation of Retrieval Augmented Generationcited by 408
  12. 2023ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledgecited by 324
7 more
  1. 2023MEDITRON-70B: Scaling Medical Pretraining for Large Language Modelscited by 272
  2. 2023HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledgecited by 161
  3. 2025MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphscited by 105
  4. 2024Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Eracited by 97
  5. 2024LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Playcited by 65
  6. 2024The Dawn of GUI Agent: A Preliminary Case Study with Claude 3.5 Computer Usecited by 62
  7. 2023AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiologycited by 34

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease Diagnosis with Multi-cohort Assessment, Fairness Analysis, and Reader Studycited by 2

Similar, not cited

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  1. 2025R-GenIMA: Integrating Neuroimaging and Genetics with Interpretable Multimodal AI for Alzheimer's Disease Progression
  2. 2026Chain-of-Thought Reasoning with Large Language Models for Clinical Alzheimer's Disease Assessment and Diagnosis
  3. 2024Profiling Patient Transcript Using Large Language Model Reasoning Augmentation for Alzheimer's Disease Detection
  4. 2026Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data
  5. 2025BRAINS: A Retrieval-Augmented System for Alzheimer's Detection and Monitoring
  6. 2025ADAM: An AI Reasoning and Bioinformatics Model for Alzheimer's Disease Detection and Microbiome-Clinical Data Integration
  7. 2025Addressing accuracy and hallucination of LLMs in Alzheimer's disease research through knowledge graphs
  8. 2025Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation