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Join the Natural Language Processing Working Group for an energetic discussion of the article Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models by Tiffany Kung et al.

Dr. Xia (Ben) Hu presents a systematic framework from modeling and application perspectives for generating DNN interpretability, aiming at dealing with main technical challenges in interpretable machine learning, i.e., faithfulness, understandability and the efficiency of interpretability.

New advances are constantly made in biomedical and health natural language processing, but very few of these advances translate to measurable impact in medicine. When new AI and NLP methodologies are used in practice, they often magnify social biases or exhibit other undesirable behaviors. These failures of translation and AI-related injustices stem from a common source.

In this presentation, Karin Verspoor introduces ideas presented in a recent JAMIA Perspective paper, grounding them in some recent examples of information extraction systems developed with clinical partners.

Dr. Virginia K. Saba was an extremely, accomplished and multifaceted nurse informaticist. However, not all nurse informaticists, especially nurses just entering informatics practice, are aware the profound impact she had on the evolution of informatics. Many informatics nurses were fortunate to have the opportunity to meet and work with Dr. Saba over the years. This webinar shared some of the most notable accomplishments of Dr. Saba as a trailblazer, mentor, and preserver of nursing informatics history.

Digital health is rapidly expanding due to surging healthcare costs, deteriorating health outcomes, and the growing prevalence and accessibility of mobile health and wearable technologies. Recent technological advancements make it possible to closely and continuously monitor individuals using multiple measurement modalities in real time.