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arXiv · 2306.10095

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

Haixing Dai·Yiwei Li·Zhengliang Liu·Lin Zhao·Zihao Wu·Suhang Song·Ye Shen·Dajiang Zhu·Xiang Li·Sheng Li·Xiaobai Yao·Lu Shi·Quanzheng Li·Zhuo Chen·Donglan Zhang·Gengchen Mai·Tianming Liu
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Abstract

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.

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Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, Xiaobai Yao, Lu Shi, Quanzheng Li, Zhuo Chen, Donglan Zhang, Gengchen Mai, Tianming Liu. 2023-06-16. AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology. https://arxiv.org/abs/2306.10095

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