Diabetes in the age of artificial intelligence

Authors

  • Alejandro Dain National University of Córdoba (UNC), Córdoba, Argentina

DOI:

https://doi.org/10.47196/diab.v59i2Sup.1255

Keywords:

artificial intelligence, diabetes

Abstract

Let us try to answer this central question: How are AI and technology revolutionizing our field of work and transforming the lives of our patients?

Artificial intelligence has emerged as a transformative force in diabetes care, primarily driven by the explosion of data generated by continuous glucose monitoring technologies. As we know, people with type 1 diabetes make up to 180 diabetes-related decisions each day—this is precisely where AI begins to demonstrate its true potential.

In the field of artificial pancreas systems, we are witnessing fascinating developments. The "Neural-network artificial pancreas" project represents a major breakthrough, with algorithms learning from each patient’s individual glycemic patterns to optimize insulin dosing decisions. This means that devices not only react but anticipate the patient's metabolic needs based on prior experiences.

Machine learning algorithms are already demonstrating over 95% accuracy in the early detection of diabetes, using techniques such as fuzzy cognitive maps and deep neural networks. These models not only predict disease but also uncover complex dynamics among risk factors that elude traditional clinical analysis.

In daily clinical practice, AI is simplifying processes that previously consumed valuable time. Tools like Mediktor show over 91% accuracy in patient triage, while platforms such as SocialDiabetes are developing algorithms that automate therapeutic decisions in patients on multiple daily injections, bringing artificial pancreas benefits to those not using insulin pumps.

However, the most promising future lies in data integration. Imagine medical records that automatically combine genomic information, wearable device data, and traditional medical records to deliver personalized precision medicine. This convergence will allow every therapeutic recommendation to be uniquely tailored to each patient.

The challenges are real: system interoperability, clinical validation of algorithms, and the need to keep healthcare professionals at the center of decision-making. But the outlook is hopeful. AI will not replace physicians—it will amplify our ability to deliver exceptional care, freeing us from repetitive tasks so we can focus on what we do best: caring for patients.

We are at the dawn of an era where technology and medical humanity converge to bring renewed hope to millions of people living with diabetes.

Author Biography

Alejandro Dain, National University of Córdoba (UNC), Córdoba, Argentina

Doctor of Medicine and Surgery, University Professor, National University of Córdoba (UNC), specialist in internal medicine, diabetes and clinical nutrition, diabetes expert

References

I. Beneyto A, Contreras I, Vehi J. Inteligencia artificial y diabetes. Revista Diabetes 2024. Disponible en: https://www.revistadiabetes.org/tecnologia/inteligencia-artificial-y-diabetes/

II. Hoyos W, Hoyos K, Ruiz-Pérez R. Modelo de inteligencia artificial para la detección temprana de diabetes. Biomédica 2023;43(Suppl 3):110-125.

III. Mackenzie SC, Sainsbury CAR, Wake DJ. Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges. Diabetologia 2024;67(2):223-235.

IV. Mohsen F, Al-Absi HRH, Yousri NA, El Hajj N, Shah Z. Artificial intelligence-based methods for precision medicine: Diabetes risk prediction. NPJ Digit Med 2024;6:197.

Published

2025-07-30

Issue

Section

SYMPOSIUM: Technology in the future