In the Algorithmic Fairness in Diabetes Prediction (ALFADIAB) project, we are researching clinical decision-making from an algorithmic perspective. We aim to audit existing models and build updated algorithms to support the equitable prognostic clinical prediction of physical and mental disease outcomes as a possible entry-point to narrowing healthcare inequalities.

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The project is funded by the Novo Nordisk Foundation.

 

Principal investigator: Associate professor Tibor V Varga

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Key publications:

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• Chakradeo K, Huynh I, Balaganeshan SB, Dollerup OL, Gade-Jørgensen H, Laupstad SK, Malham M, Nguyen TL, Hulman A, Varga TV (2025). “Navigating fairness aspects of clinical prediction models”. BMC Medicine 23(1): 567. Link

• Thomsen HB, Li LY, Isaksen AA, Lebiecka-Johansen B, Bour C, Fagherazzi G, van Doorn WPTM, Varga TV, Hulman A (2025). “Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes”. PLOS Digital Health 4(6): e0000918. Link

• Varga TV (2023). "Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities". Open Heart 10(2): e002395. Link

• Cronjé HT, Katsiferis A, Elsenburg LK, Andersen TO, Rod NH, Nguyen TL, Varga TV (2023). “Assessing racial bias in type 2 diabetes risk prediction algorithms”. PLOS Global Public Health 3(5): e0001556. Link