The Future of Healthcare: How AI and ChatGPT are Changing the Game in Medicine
Zhiyong Lu
March 8, 2024, Friday, 2:00 PM - 3:00 PM EST
The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating their uses in some real-world applications such as improving PubMed searches (Fiorini et al., Nature Biotechnology 2018), supporting precision medicine (Allot et al., Nature Genetics 2023), and taming COVID-19 pandemic paper tsunami in LitCovid (Chen et al., Nature 2000), we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery.
Dr. Zhiyong Lu is Senior Investigator with tenure at the NIH Intramural Research Program, leading research in biomedical text and image processing, information retrieval, and AI/machine learning. In his role as Deputy Director for Literature Search at National Center of Biotechnology Information (NCBI), Dr. Lu oversees the overall R&D efforts to improve literature search and information access in resources like PubMed and LitCovid that are used by millions worldwide on a daily basis. Additionally, Dr. Lu holds an Adjunct Professor position with the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC).

Dr. Lu is a Fellow of the American College of Medical Informatics (ACMI) and the International Academy of Health Sciences Informatics (IAHSI). Over the years, Dr. Lu has mentored over 70 trainees and is a highly cited author with over 350 peer-review articles in leading scientific journals such as Nature, Nature Biotechnology, Nature Genetics, PLoS Biology, etc. According to Google Scholar, he has an h-index of 75 with over 35,000 citations. His many recent publications and invited talks generally have a focus on the following topics: Biomedial Literature Search (e.g. PubMed Best Match, LitCovid); AI & LLMs (e.g. GeneGPT, TrialGPT); NLP & Text Mining (e.g. PubTator, BioCreative, LitVar); Medical image processing (e.g. NIH Chest X-ray Dataset, DeepSeeNet)