Advancing critical care with artificial intelligence

Dates and Times

Start: 4/29/2026 8:00 AM
End: 4/29/2026 9:00 AM

Objectives

Describe emerging applications of artificial intelligence in critical care, including machine learning models that may help predict clinical events such as extubation readiness, ventilator-associated pneumonia, and outcomes in community-acquired pneumonia.

Explain developing data infrastructures and analytic approaches in ICU medicine, including longitudinal datasets, federated analysis, and transition-state modeling.

Discuss potential benefits and current limitations of AI in healthcare, including the use of large language models for clinical documentation and summarization, and challenges related to bias, privacy, and accuracy.

Speakers

Accreditation

The School of Medicine, State University of New York at Stony Brook, is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The School of Medicine, State University of New York at Stony Brook designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credits ^™. Physicians should only claim the credit commensurate with the extent of their participation in the activity.

Maintenance of Certification

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 1.00 MOC points in the American Board of Internal Medicine’s (ABIM) Maintenance of Certification (MOC) program. Participants will earn MOC points equivalent to the amount of CME credits claimed for the activity. It is the CME activity provider’s responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit.