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Machine Learning Model Accurately Predicts Long-Term Risk of Type 2 Diabetes
The model used data from 3.4 million adults and showed strong accuracy for predicting type 2 diabetes risk up to 10 years ahead, researchers said.
- Researchers presented a machine-learning model predicting 10-year Type 2 diabetes risk at the American Diabetes Association's 2026 Scientific Sessions in New Orleans on Friday.
- Over 60% of U.S. adults possess risk factors for Type 2 diabetes, overwhelming current prevention programs; diabetes often develops gradually without clear warning signs, complicating early identification.
- The retrospective study analyzed clinical data from over 3 million adults at Kaiser Permanente Northern California, achieving an area under the curve of 0.886 in high-risk identification.
- "These findings represent a potential advancement over existing approaches," said lead author Luis A. Rodriguez, PhD, MPH, RD, enabling earlier, more precise detection for clinicians.
- Researchers intend to test the model in clinical settings to evaluate whether it increases prevention program engagement and reduces diabetes incidence.
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Total News Sources35
Leaning Left4Leaning Right1Center20Last UpdatedBias Distribution80% Center
Bias Distribution
- 80% of the sources are Center
80% Center
L 16%
C 80%
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