The future of healthcare is happening

Taha Kass-Hout takes the Main Stage

Dr. Taha Kass-Hout
Global Chief Science & Technology Officer, GE HealthCare

Monday, October 21st, 9:00-9:20 am Main Stage

Discover pivotal insights shaping the future of healthcare. Widely-acknowledged healthcare technology and AI thought leader Dr. Taha Kass-Hout, MD, MS is the Global Chief Technology Officer at GE HealthCare, and leads our efforts to revolutionize how healthcare is delivered and managed with advanced AI and digital solutions.

Unleashing the Power of Foundation Models

Parry Bhatia
Chief AI Officer, GE HealthCare

Tuesday, October 22nd, 11:10-11:30 AM AI @ HLTH Stage B

Traditionally, AI integration in healthcare requires costly and complex model retraining. But Foundation Models are large-scale neural networks that can be reused and fine-tuned for various tasks with pre-training.

This innovative approach could streamline workflows in healthcare, where acquiring labeled data is particularly time consuming and costly, enhancing patient care and operational efficiencies.

Tech Talk: Multimodal Models as the Future Healthcare Companion

Danica Xiao
Vice President, AI, GE HealthCare

Tuesday, October 22nd, 3:15–3:25 PM Tech Talk Stage

This talk will explore the cutting-edge innovations in Large Language Models, Multimodal Models, and Generative AI developed by GE HealthCare. We will explore how these future technologies aim to synergize a diverse range of data types, adapt to varied user needs, and provide comprehensive insights to support healthcare professionals by reducing cognitive burden, driving operational efficiency, and simplifying multidisciplinary decision making.

Duke Health achieves sustainable results by leveraging machine learning

Kristie Barazsu
Associate Chief Operating Officer – Emergency Services, Patient Flow & Support Services
Duke University Hospital

Bree Bush
GM & VP, Command Center & Pharma Solutions
GE HealthCare

Monday, Oct 21st, 11:35-11:55 am AI @ HLTH Stage B

Health systems struggle to manage patient flow and capacity due to unstructured data across multiple systems. We’ll explore real world examples of GE HealthCare collaborations where machine learning models have helped streamline operational decisions and improved access to care.