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Explore AMIA’s Newest Conference: Amplify Informatics

Type
Member Interests
Explore AMIA’s newest conference, Amplify Informatics. Learn how this dynamic gathering empowers informatics professionals, researchers, clinicians, and health IT leaders with cross-domain education, networking opportunities, and real-world impact insights designed to advance healthcare innovation and collaboration.
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JAMIA Journal Club Webinar - February 2026

Type
JAMIA Journal Club
Credits
1.00
CME
1.00
CNE
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 [...]

Members Only

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Informatics Careers in the Secondary Use of Clinical Data for Research

Type
Careers in Informatics
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 [...]
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Unlocking Biomedical Research Data Resources from the National Library of Medicine

Type
Policy
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.
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JAMIA Journal Club Webinar - December 2025

Type
Webinar
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 [...]