Search AMIA.org

This webinar discusses pros, cons and challenges of moving health informatics research from silos and registry-centric to multi-centric electronic health records data. It will provide tools and data science methods incorporated to mine electronic health records to extract and capture time-dependent features when equally-spaced time is not present. The goal [...]

A significant portion of data in the healthcare industry exists as narrative text, such as clinical notes in electronic health record (EHR) systems, clinical trial descriptions, biomedical literature, and consumer-generated content on social media and online forums. With the advancements in Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques, valuable insights, such as symptoms and causal relationships between medical concepts, can be extracted from various text data to aid in clinical decision-making and improve healthcare outcomes.

The dream of precision health is to develop a data-driven, continuous learning system where new health information is instantly incorporated to optimize care delivery and accelerate biomedical discovery. In reality, the health ecosystem is plagued by overwhelming unstructured data and unscalable manual processing. Self-supervised AI such as large language models (LLMs) can supercharge structuring of biomedical data and accelerate transformation towards precision health

This practical webinar will look at what mentoring is, and why it can make a difference. Mentoring has long been recognized as a powerful tool in career development. Research backs this, showing mentored individuals to have higher career satisfaction and greater commitment to their profession than non-mentored individuals. Additionally, the mentoring relationship can benefit both parties providing multiple rewards.

This session will present the work of a community of practice supported by the Gordon and Betty Moore foundation to promote the use of NLP “at-scale” in CQM used in accountability programs.

Join the Natural Language Processing Working Group for a talk from Dr. Trevor Cohen on Probing the Dimensions of Meaning in Medicine with Distributed Representations of Biomedical Language.