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In Vitro to in Vivo Translation of Artificial Intelligence for Clinical Use: Screening for Acute Coronary Syndrome to Identify ST-Elevation Myocardial Infarction Read the abstract Presenter Moderator Statement of Purpose Despite rapid growth in the development of clinical prediction models, methodological guidance for their technical translation from desktop, in vitro [...]

Access microlearning modules from AMIA’s industry-leading educational conferences through an on-demand, personalized streaming experience designed to keep you up to date with the latest in health informatics learning.

Discover how the relaunched NLM Dataset Catalog improves the discoverability and reuse of biomedical research data supported by the NIH. This webinar explores how the National Library of Medicine’s centralized platform enables researchers to search, find, and connect high-value datasets across multiple repositories, strengthening research rigor, reproducibility, and data sharing. Learn about recent enhancements informed by user feedback and current efforts to expand access to NIH-funded research data.

The promise of secondary use of clinical data — from population health to clinical trial matching — often fails due to the reality of data quality. This session presents an end-to-end framework for converting fragmented, multimodal clinical data into audit-ready, high-fidelity data assets.

This webinar explores career paths built around the secondary use of clinical patient data for research. The panelists will describe how real-world clinical data are transformed into research-ready assets and used to support observational studies, clinical trial feasibility, and evidence generation across industry and academia. The session includes an overview [...]

Dynamic Few-Shot Prompting for Clinical Note Section Classification Using Lightweight, Open-Source Large Language Models Read the abstract Moderator Presenter Statement of Purpose Critical information about patient care is locked behind context-sensitive, domain-specific language of clinical note text. Detecting the structure of this clinical text has been demonstrated to enhance extraction [...]