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The Student Working Group's (STWG) monthly meeting is a perfect place to get involved! The STWG wants your input on how to improve student involvement through offsite activities, career guidance panels, grant advice sessions, and more! Work together to make AMIA meetings and membership more valuable and rewarding for our [...]

Information retrieval (IR) has been a dominant force in the last 20 years of computing. Even within the domain of natural language processing (NLP), tasks such as summarization and question answering have come a long way based on IR-like approaches designed to surface information that already exists.

This Surgical and Procedural Informatics Discussion group will describe challenges and potential solutions to the use of non-human authors in peer-reviewed literature and will introduce emerging evidence that large language models have the potential to change surgical care.

Dr. Jackie Gerhart, VP of Clinical Informatics and Epic Clinician shares details on the current state and research potential nation's largest EHR data collaboration platform. Watch the Recording Presenter Jacqueline Gerhart, MD is a family medicine physician and clinical informaticist at Epic in Verona, WI. She earned her medical degree [...]

Dr. Heidi Hanson discusses a National Cancer Institute (NCI) and Department of Energy collaboration to develop computational modeling and artificial intelligence approaches to advance cancer research. This work is related to the Blue-Ribbon Panel recommendation to build a national cancer data ecosystem.

The explosion of biomedical big data and information in the past decade created new opportunities for discoveries to improve the treatment and prevention of human diseases. But the large body of knowledge presents a grand new challenge. Individual scientists around the world are increasingly finding themselves overwhelmed by the sheer volume of research literature and are struggling to keep up to date and to make sense of this wealth of textual information.

This webinar summarizes current trends and use cases that apply state-of-the-art natural language processing in healthcare systems, pharmaceuticals, and health IT companies. David Talby covers unlocking use cases that become possible with current large language models; enabling medical domain experts to train & tune models in a co-code environment; and testing NLP models across aspects of Responsible AI in preparation for regulatory oversight. Talby also shares free and open-source tools that you can use today in these three areas.