Department of Applied Computing tenure-track faculty candidate Wenqi Shi will give a research presentation on Wednesday, March 27, 2024, at 1 pm in Fisher 127. The title of Shi’s talk is, “Advancing Personalized Medicine Through Generative Artificial Intelligence.”
The event was rescheduled from its original time, date, and location of March 26 at 1 pm in Rekhi 214.
Talk Abstract
The primary goal of next-generation healthcare systems is to deliver preventive, predictive, precise, participatory, and personalized health, thereby improving the quality of patient care. The objective of this presentation is to advance cutting-edge AI-enabled clinical decision support systems (CDSS), including large language models, to facilitate translational personalized medicine. Firstly, we investigate data-centric AI methods to prepare integrative, large-scale, and high-quality patient data to address data scarcity and quality issues, with a specific focus on rare diseases. Secondly, we develop an AI-enabled CDSS framework for improved patient care by solving responsible AI considerations, including model transparency, accountability, trustworthiness, and fairness. Thirdly, with the emerging few-shot capabilities of LLMs in reasoning and planning, we deploy translational and interactive LLM-based agents for improved user experience in real-world clinical practice. Specifically, clinicians can specify tasks in natural language, and the LLM agent autonomously generates and executes code to interact with EHRs for answers, eliminating the need for specialized expertise or extra effort from data engineers in conventional clinical settings. LLM- based agents enable simple and efficient interactions among clinicians, EHR systems, and external tools, simplifying clinical workload and reducing additional burdens when introducing new tools. By advancing emerging AI in personalized medicine, the proposed framework aims to bridge the gap between biomedical research and clinical practice, thereby promoting the adoption of AI in real- world clinical practice.
Candidate Bio
Wenqi Shi is a Ph.D. candidate at the School of Electrical and Computer Engineering from Georgia Institute of Technology. Her research interests mainly focus on developing cutting- edge precision medicine pipelines using responsible AI to facilitate translational clinical research, especially for shared decision-making with pediatric patients and their families. With the ultimate goal of translation research, the impact of her work extends beyond academia; she has collaborated with clinicians from Shriners Children’s, CHOA, VA, and Emory Hospital to develop and deploy clinical decision support systems to facilitate real-world clinical research and practice. She has also received the EECS Rising Star 2023 and ACM BCB SIGBio Best Paper Award during her Ph.D. study.