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AI-powered Risk Stratification in Type 1 Diabetes

Dr Gun Forsander discusses how AI-powered risk stratification may be utilized to optimize T1D screening strategies 

Learning Objectives

  • Highlight AI-driven strategies from other therapy areas in disease identification and screening
  • Communicate how AI-driven analysis could enhance T1D risk prediction

Summary

We know that AI algorithms have outperformed traditional methods in identifying individuals at high risk of cancer, cardiovascular diseases, neurodegenerative diseases, and even type 2 diabetes. AI can predict type 2 diabetes risk more accurately than a traditional logistic regression-based model based on genetics and clinical factors and metabolite data.

So, this is a question: Can AI powered risk certification optimize even type 1 diabetes screening strategies? Yes, we think it can. An AI algorithm in type 1 diabetes can integrate diverse data sources from environment, genetics, biomarkers and new variables and produce individualized risk scores, which of course, is very interesting when discussing screening strategies. So, AI generated risk profiles could be used to inform who to screen from the general population.

Gun Forsander Screening Stages of T1D

MAT-GLB-2501740-1.0 05/2025