Monday, February 23, 2026 | Monday, March 2, 2026
5:30PM-7:00PM
Venue
This will be a two-part virtual event. Login information will be included in your confirmation email.
The event is free; advance registration is required.
Register
Wednesday, November 5, 2025
5:00PM-7:30PM
Venue
The New York Academy of Medicine
1216 Fifth Avenue at 103rd Street
New York, NY 10029
$25 Registration fee; $10 Students
Refreshments will be provided.
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Effective care of acutely ill patients requires assessment and diagnostic skills and attentive monitoring of their clinical status. These skills are not the property of any one clinical discipline. Recent research has reported advances on the use of AI and large language models (LLM) to enhance practitioner effectiveness in these areas. A multidisciplinary program designed to be of interest to all healthcare practitioners, will offer internationally recognized experts who will illuminate the advances and challenges posed by these applications in practice.
The panel presentations will highlight recent advances in the use of AI to enhance the accuracy of clinical diagnosis and to accelerate recognition of emergent clinical deterioration among hospitalized patients. They will illuminate the research supporting these developments. They will also emphasize the challenges inherent in bringing them to bear on real-world practice. Attendees will be provided tips on how to identify and navigate trustworthy AI resources in practice.
The program will be preceded by an expo featuring live exhibits and demonstrations of available and developing AI resources. Refreshments will be available to attendees.
Abstract submissions must follow these guidelines: Include a title, list of authors with affiliations, and a structured abstract (maximum 500 words) detailing purpose, methods, results, and conclusions/implications. Please find more information below:
Agenda
5:00–6:00 PM – Expo & Reception (including poster sessions and hands-on demonstrations of AI products and programs)
6:00–7:30 PM – Speaker Panel
Speakers
Kenrick Cato, PhD, RN, CPHIMS, FAAN
Kenrick Cato, PhD, RN, CPHIMS, FAAN, is a clinical informatician whose research focuses on mining electronic patient data to support decision-making for clinicians, patients, and caregivers. Operationally, he spends his time mining and modeling Nursing data to optimize Nursing value in Healthcare. He is also involved in several national-level informatics organizations, including as a board member of the American Medical Informatics Association (AMIA), Chair of the Nursing Informatics Working Group(NIWG) of AMIA, as well as a convening member of the AMIA-sponsored 25 x 5 initiative to reduce documentation burden. Dr. Cato received his BSN, MS, and Ph.D. in Clinical informatics at Columbia University. He is co-principal investigator on the Communicating Narrative Concerns Entered by RNs (CONCERN) Early Warning System.
Geoff Norman
Geoff Norman is Professor Emeritus of the Department of Clinical Epidemiology and Biostatistics at McMaster University. He received a Ph.D. in nuclear physics from McMaste in 1971, and a M.A. in educational psychology from Michigan State in 1977.
He has a long-standing interest is in cognitive psychology applied to clinical reasoning, learning, and decision-making.. He has published over 300 peer-reviewed papers and over 30 books and book chapters and has received numerous national and international awards.
Dr. Matthew Sibbald MD MHPE PhD FRCPC
Dr. Matthew Sibbald MD MHPE PhD FRCPC is an interventional cardiologist, Associate Dean of Undergraduate Medical Education, and educational scientist at McMaster University. He holds a master’s and PhD from Maastricht University, Netherlands in Health Professions Education. He leads Canada’s largest three-year MD program, with a focus on integrating AI. His scholarship includes research on cognitive load, clinical judgment, and the use of AI in practice and assessment.
Ashley Beecy MD, FACC
Ashley Beecy MD, FACC is currently the Chief AI Officer for Sutter Health in California. Previously she served as Medical Director of Artificial Intelligence (AI) Operations at New York Presbyterian, where she was responsible for the governance, evaluation and implementation of clinical AI models. She is also a practicing cardiologist. Her research focus is in digital health, including the safe and effective use of AI in healthcare. Dr. Beecy earned her medical degree from Albert Einstein College of Medicine and completed her Internal Medicine residency at New York Presbyterian/Weill Cornell Medicine. Prior to a career in medicine, Dr. Beecy spent 10 years working in industry. As an electrical engineer at IBM, she was responsible for the physical design of chip level architectures.
Venue
This will be a virtual event. Login information will be included in your confirmation email.
The event is free; advance registration is required.
Register
Artificial intelligence is redefining the landscape of healthcare, and nursing must stand at the forefront of this transformation. This session illuminates the profound implications of AI for hospitals and nursing schools, offering leaders a clear vision of how AI is being used, equipping faculty with strategies to prepare the next generation of nurses, and empowering students to graduate with the knowledge and skills to excel academically, clinically, and as future leaders. By unmasking AI, we position nursing not only to adapt to change but to shape it, ensuring the profession remains a driving force in improving outcomes and advancing health equity. Forward thinking nursing leaders, educators, and students will want to attend.
Through interactive Ted-style talks and hands-on breakout sessions, attendees will gain practical strategies to integrate AI into hospital leadership, curriculum development, and academic success. This essential event empowers nursing professionals not just to adapt to AI-driven change, but to actively shape the future of healthcare while advancing patient outcomes and health equity.
Speakers
Dr. Olga Kagan
Olga Kagan, PhD, RN, FHIMSS, FAAAAI, FIEL, is a nurse educator, scientist and entrepreneur. She teaches at two New York-based universities, contributes to textbooks, mentors nurses, and advises start-ups. Dr. Kagan founded the Food Allergy Nursing Interest Professional Group and co-founded SONSIEL’s Collaborative Healthcare Innovation, Research & Problem Solving (CHIRPS). As a recognized thought leader, she has served on several committees and boards in various positions, including with HIMSS, SONSIEL, ANA, NYAM, AAAAI, and ENRS. She has received multiple awards for her contributions to nursing leadership, mentorship, research, and was featured on HIMSS TV, the AAAAI and Outcomes Rocket podcasts.
Dr. Kathleen McGrow
Dr. Kathleen McGrow is the Global Chief Nursing Innovation Officer at Microsoft, where she leads strategic initiatives in digital health transformation. Her work focuses on addressing workforce challenges, enhancing patient and provider engagement, and advancing cognitive computing to support a learning health system.
Dr. McGrow earned her Doctor of Nursing Practice from the University of Maryland, Baltimore. With a background in trauma critical care and health IT, she brings deep expertise to the intersection of clinical practice and emerging technologies. She is a recognized thought leader in the application of artificial intelligence in healthcare, with notable publications including “Foundation Models, Generative AI, and Large Language Models: Essentials for Nursing” and “Implications of Artificial Intelligence for Nurse Managers.” Her most recent work is her book, “Empowering Nurses with Technology: A Practical Guide to Nurse Informatics,” published in January 2025.
In addition to her role at Microsoft, Dr. McGrow co-chairs the HIMSS Nursing Innovation Advisory Committee and serves as an adjunct clinical instructor at the University of Alabama at Birmingham School of Nursing.
Dr. Delaney La Rosa
Delaney La Rosa, EdD, MSN Ed, RN, is an educator and academic leader bridging clinical practice, digital innovation, and equity-centered curriculum, with extensive experience in program evaluation and accreditation that has shaped transformative nursing education. Formerly the Associate Dean of Nursing and Steinbronn Endowed Professor at Northern Arizona University, Dr. La Rosa led initiatives in inclusive teaching, AI integration in healthcare education, and faculty development, with a teaching focus on healthcare informatics, leadership, and AI. Nationally recognized for research and speaking on ethical AI in nursing and education, their scholarship aligns emerging technologies with human-centered, accessible approaches, including recent work on AI literacy for nurses and equitable learning models, and contributions to national frameworks for AI adoption in nursing. Dr. La Rosa has also played a key role in CCNE and state board accreditation reviews, ensuring curriculum alignment with national standards and demonstrating expertise in outcomes-based assessment, curriculum mapping, and quality improvement for accreditation readiness, all while dedicated to advancing the nursing profession through digital innovation, education, and research at FSU.