# AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology

arXiv: https://arxiv.org/abs/2306.10095 · HTML: https://mlsanity.com/paper/2306.10095/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 55 references that are in the map.
- First posted on arXiv 16 Jun 2023.

## Builds on (most cited first, 21 of 21)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [PaLM: Scaling Language Modeling with Pathways](https://mlsanity.com/paper/2204.02311/) (2022)
- [Fine-Tuning Language Models from Human Preferences](https://mlsanity.com/paper/1909.08593/) (2019)
- [BLOOM: A 176B-Parameter Open-Access Multilingual Language Model](https://mlsanity.com/paper/2211.05100/) (2022)
- [PaLM 2 Technical Report](https://mlsanity.com/paper/2305.10403/) (2023)
- [Improving alignment of dialogue agents via targeted human judgements](https://mlsanity.com/paper/2209.14375/) (2022)
- [Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models](https://mlsanity.com/paper/2304.03738/) (2023)
- [AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing](https://mlsanity.com/paper/2108.05542/) (2021)
- [DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4](https://mlsanity.com/paper/2303.11032/) (2023)
- [Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision](https://mlsanity.com/paper/1611.00020/) (2016)
- [On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence](https://mlsanity.com/paper/2304.06798/) (2023)
- [When Brain-inspired AI Meets AGI](https://mlsanity.com/paper/2303.15935/) (2023)
- [Spear Phishing With Large Language Models](https://mlsanity.com/paper/2305.06972/) (2023)
- [Differentiate ChatGPT-generated and Human-written Medical Texts](https://mlsanity.com/paper/2304.11567/) (2023)
- [Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions](https://mlsanity.com/paper/2105.09392/) (2021)
- [Intersectional Bias in Causal Language Models](https://mlsanity.com/paper/2107.07691/) (2021)
- [AGI for Agriculture](https://mlsanity.com/paper/2304.06136/) (2023)
- [AGI: Artificial General Intelligence for Education](https://mlsanity.com/paper/2304.12479/) (2023)

## Built on by (most cited first, 30 of 34)

- [Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security](https://mlsanity.com/paper/2401.05459/) (2024)
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- [Large Language Models for Robotics: Opportunities, Challenges, and Perspectives](https://mlsanity.com/paper/2401.04334/) (2024)
- [Review of Large Vision Models and Visual Prompt Engineering](https://mlsanity.com/paper/2307.00855/) (2023)
- [Understanding LLMs: A Comprehensive Overview from Training to Inference](https://mlsanity.com/paper/2401.02038/) (2024)
- [MARFT: Multi-Agent Reinforcement Fine-Tuning](https://mlsanity.com/paper/2504.16129/) (2025)
- [Radiology-Llama2: Best-in-Class Large Language Model for Radiology](https://mlsanity.com/paper/2309.06419/) (2023)
- [GeoGPT: Understanding and Processing Geospatial Tasks through An Autonomous GPT](https://mlsanity.com/paper/2307.07930/) (2023)
- [Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research](https://mlsanity.com/paper/2412.04497/) (2024)
- [Segment Anything Model (SAM) for Radiation Oncology](https://mlsanity.com/paper/2306.11730/) (2023)
- [Large Language Models for Manufacturing](https://mlsanity.com/paper/2410.21418/) (2024)
- [Holistic Evaluation of GPT-4V for Biomedical Imaging](https://mlsanity.com/paper/2312.05256/) (2023)
- [RadOnc-GPT: A Large Language Model for Radiation Oncology](https://mlsanity.com/paper/2309.10160/) (2023)
- [Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning](https://mlsanity.com/paper/2402.00251/) (2024)
- [On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications](https://mlsanity.com/paper/2312.17016/) (2023)
- [Evaluating Large Language Models for Radiology Natural Language Processing](https://mlsanity.com/paper/2307.13693/) (2023)
- [Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models](https://mlsanity.com/paper/2309.17319/) (2023)
- [Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation](https://mlsanity.com/paper/2411.11295/) (2024)
- [GP-GPT: Large Language Model for Gene-Phenotype Mapping](https://mlsanity.com/paper/2409.09825/) (2024)
- [Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios](https://mlsanity.com/paper/2411.14461/) (2024)
- [Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey](https://mlsanity.com/paper/2504.14520/) (2025)
- [Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities](https://mlsanity.com/paper/2310.19626/) (2023)
- [Ophtha-LLaMA2: A Large Language Model for Ophthalmology](https://mlsanity.com/paper/2312.04906/) (2023)
- [Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review](https://mlsanity.com/paper/2311.01918/) (2023)
- [Large Language Model Based Multi-Agent System Augmented Complex Event Processing Pipeline for Internet of Multimedia Things](https://mlsanity.com/paper/2501.00906/) (2025)
- [Evaluating Mathematical Reasoning Across Large Language Models: A Fine-Grained Approach](https://mlsanity.com/paper/2503.10573/) (2025)
- [Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification](https://mlsanity.com/paper/2307.04343/) (2023)
- [GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science](https://mlsanity.com/paper/2312.03769/) (2023)
- [Evaluating multiple large language models in pediatric ophthalmology](https://mlsanity.com/paper/2311.04368/) (2023)
- [PharmacyGPT: The AI Pharmacist](https://mlsanity.com/paper/2307.10432/) (2023)

## Abstract (arXiv)

In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which can conduct data collection, processing, and analysis about complex health narratives of Alzheimer's Disease in an autonomous manner via users' textual prompts. We collated comprehensive data from a variety of news sources, including the Alzheimer's Association, BBC, Mayo Clinic, and the National Institute on Aging since June 2022, leading to the autonomous execution of robust trend analyses, intertopic distance maps visualization, and identification of salient terms pertinent to Alzheimer's Disease. This approach has yielded not only a quantifiable metric of relevant discourse but also valuable insights into public focus on Alzheimer's Disease. This application of AD-AutoGPT in public health signifies the transformative potential of AI in facilitating a data-rich understanding of complex health narratives like Alzheimer's Disease in an autonomous manner, setting the groundwork for future AI-driven investigations in global health landscapes.