The Role of Digital Twin AI Models in Diabetes Care and Remission

The Role of Digital Twin AI Models in Diabetes Care and Remission | Recording

ADA Member Exclusive Recorded Webinar

In the era of precision medicine, Digital Twin AI platforms are transforming diabetes care by creating virtual representations of individual patients. These platforms integrate multimodal data sources—such as continuous glucose monitoring (CGM), lifestyle inputs, and biomarkers—to provide real-time insights and predictive modeling. By simulating personalized scenarios, Digital Twins enable clinicians and patients to optimize treatment strategies, improve glycemic control, and reduce complications through highly individualized care plans.

Overview

In the era of precision medicine, Digital Twin AI platforms are transforming diabetes care by creating virtual representations of individual patients. These platforms integrate multimodal data sources—such as continuous glucose monitoring (CGM), lifestyle inputs, and biomarkers—to provide real-time insights and predictive modeling. By simulating personalized scenarios, Digital Twins enable clinicians and patients to optimize treatment strategies, improve glycemic control, and reduce complications through highly individualized care plans.

Learning Objectives

Explain the concept of Digital Twin AI and its application in precision medicine for diabetes management.
Analyze the role of integrated data streams (CGM, lifestyle inputs, biomarkers) in enhancing predictive accuracy and personalization of diabetes care.

Speaker

Rohit S Warrier, MS, DABRM, MSc, EBEEDM
Senior, Fellow, International Diabetes Federation

Moderator

Maria Bettini, PhD
Professor of Pathology, University of Utah

Summary

Availability:

On-Demand

Expires on Mar 12, 2028

Cost:

FREE

Credit Offered:

1 CME Credit

1 ABIM-MOC Point

1 ACPE Credit

1 ANCC Credit

1 AAPA Credit

1 CDR Credit

1 APA Credit

1 ASWB Credit

1 COP Credit

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