Li-Kuo Kuo

20th September 2026 Sunday

Time	Session

14:00 15:30	Evaluating Generative AI in the ICU Chun-Fu Lai Moderator Li-Kuo Kuo Moderator Clinical Support Information with Generative AI: Content Generation and Evaluation Yu-Chang YEH Speaker Clinical Support Information with Generative AI: Content Generation and Evaluation Generative artificial intelligence is shifting from single-question answering toward structured clinical decision support at the bedside. This lecture presents a practical approach to generating and evaluating AI-derived clinical support information in critical care. On the generation side, we describe a multi-turn conversation and multi-task workflow in which structured patient data, a machine learning mortality prediction model, and SHAP-based explanations are passed sequentially to a large language model through five linked task prompts covering risk interpretation, syndrome identification, current status and diagnoses, recommended examinations, and management suggestions. Each turn inherits the context of the previous one, so the output accumulates into a coherent clinical narrative rather than a set of isolated answers. On the evaluation side, we introduce the IMPACT Framework, a six-domain, 21-item instrument developed through a multinational Delphi consensus involving 58 panelists from 12 countries. Its domains, Integration, Mastery, Precision, Applicability, Comprehensiveness, and Timeliness, allow both clinicians and automated judges to score generated content reproducibly. We share validation results, examples from an intensive care cohort, and lessons learned from iterative prompt refinement. Attendees will leave with a transferable method for building and auditing generative AI support tools in their own units. AI-Assisted Reference Management and Graphical Abstract Creation Yu-Chen Chuang Speaker AI-Assisted Reference Management and Graphical Abstract CreationBy the end of this case-based learning session, participants will be able to apply the IMPACT framework to systematically evaluate the appropriateness, reliability, and potential risks of generative AI tools in ICU clinical contexts, while using AI-assisted workflows for reference management and graphical abstract creation to enhance research communication and citation potential. Room 5

Time

Session

14:00

15:30

Evaluating Generative AI in the ICU

Chun-Fu Lai Moderator

Li-Kuo Kuo Moderator

Clinical Support Information with Generative AI: Content Generation and Evaluation

Yu-Chang YEH Speaker Clinical Support Information with Generative AI: Content Generation and Evaluation Generative artificial intelligence is shifting from single-question answering toward structured clinical decision support at the bedside. This lecture presents a practical approach to generating and evaluating AI-derived clinical support information in critical care. On the generation side, we describe a multi-turn conversation and multi-task workflow in which structured patient data, a machine learning mortality prediction model, and SHAP-based explanations are passed sequentially to a large language model through five linked task prompts covering risk interpretation, syndrome identification, current status and diagnoses, recommended examinations, and management suggestions. Each turn inherits the context of the previous one, so the output accumulates into a coherent clinical narrative rather than a set of isolated answers. On the evaluation side, we introduce the IMPACT Framework, a six-domain, 21-item instrument developed through a multinational Delphi consensus involving 58 panelists from 12 countries. Its domains, Integration, Mastery, Precision, Applicability, Comprehensiveness, and Timeliness, allow both clinicians and automated judges to score generated content reproducibly. We share validation results, examples from an intensive care cohort, and lessons learned from iterative prompt refinement. Attendees will leave with a transferable method for building and auditing generative AI support tools in their own units.
AI-Assisted Reference Management and Graphical Abstract Creation

Yu-Chen Chuang Speaker AI-Assisted Reference Management and Graphical Abstract CreationBy the end of this case-based learning session, participants will be able to apply the IMPACT framework to systematically evaluate the appropriateness, reliability, and potential risks of generative AI tools in ICU clinical contexts, while using AI-assisted workflows for reference management and graphical abstract creation to enhance research communication and citation potential.

Room 5