Beyond the Hype: When, Where and What Artificial Intelligence Tools to Use in Otolaryngology

Tuesday, October 20, 2026

11:15 AM - 12:15 PM PT

Location: 402A

Moderator(s)

BD

Brian D. D'Anza, MD

Associate Professor, Attending Surgeon, System Medical Director Digital Health
Case Western Reserve University/ University Hospital Case Medical Center
Cleveland, Ohio, United States

Panelist(s)

BL

Brian C. Lobo, MD, ABPM-CI, FARS

Chief Medical Informatics Officer/Assoc Professor
UF Health
Gainesville, FL, United States
Sanjeet V. Rangarajan, MD

Associate Professor and Vice Chair - Innovation and Community Partnerships
University Hospitals Cleveland Medical Center
Cleveland, OH, United States
ZP

Zara M. Patel, MD

Professor
Stanford University School of Medicine
Stanford, California, United States

Disclosure(s):

Sanjeet V. Rangarajan, MD:

faculty for this accredited education activity has no relationship(s) with ineligible companies to disclose.

Whether it is for clinic efficiencies, patient diagnosis, therapies or patient engagement, AI is becoming a critical component of how otolaryngologists take care of patients. This session will describe specific applications that any otolaryngologist can use to benefit their practice. This includes panelists describing the use of public facing generative AI, natural language processing solutions as well as more specialized machine learning (ML) programs. Practical, real-world examples will be presented by the panelists, including AI for documentation, answering patient messages, and diagnostics, among others. Join to learn about the future of AI in otolaryngology so you can stay up to date and at the cutting edge of care.

Learning Objectives:

Recognize the importance of using AI technologies in clinical settings, including both public-facing large language models (LLMs), natural language processing, and pathology specific machine learning algorithms
Discuss three applications of AI that can be used within an otolaryngologist’s day-to-day life to improve the efficiency of documentation, diagnosis, and therapy
Analyze when and where specific AI tools can be used in practice, including cloud-based technologies and mobile applications