Artificial Intelligence in the Early Detection and Precision Management of  Type 2 Diabetes: Integrating Genomics, Digital Health, and Clinical Decision  Systems

Hammad Ahmed Bhatti, Zoha JavedShahid Hamid, Madiha Raheel, Nadeem Raza, Najm ul saqib, Nain Tara, Akhil Ramanujam Chakravartula

Artificial Intelligence in the Early Detection and Precision Management of Type 2 Diabetes: Integrating Genomics, Digital Health, and Clinical Decision Systems

Authors

Hammad Ahmed Bhatti, Zoha JavedShahid Hamid, Madiha Raheel, Nadeem Raza, Najm ul saqib, Nain Tara, Akhil Ramanujam Chakravartula

Keywords:

Artificial intelligence, Type 2 diabetes mellitus, precision medicine, polygenic risk scores, clinical decision support systems, digital health, continuous glucose monitoring.

Abstract

Background: Type 2 diabetes mellitus(T2DM) poses a profound global publichealth challenge, characterized by complexinteractions between genetic predisposition, environmental influences, and lifestylefactors. Traditional care paradigms

References

1. Cole, J. B., & Florez, J. C. (2020). Genetics of diabetes mellitus and diabetes complications. Nature Reviews Nephrology, 16(7), 377–390.

2. Sun, H., Saeedi, P., Karuranga, S., Pinkepank, M., Ogurtsova, K., Duncan, B. B., ... & Magliano, D. J. (2022). IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Research and Clinical Practice, 183, 109119.

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Published

2026-10-21

How to Cite

Hammad Ahmed Bhatti, Zoha JavedShahid Hamid, Madiha Raheel, Nadeem Raza, Najm ul saqib, Nain Tara, Akhil Ramanujam Chakravartula. (2026). Artificial Intelligence in the Early Detection and Precision Management of Type 2 Diabetes: Integrating Genomics, Digital Health, and Clinical Decision Systems. International Journal of Pharmacy Research & Technology (IJPRT), 16(2), 6778–6787. Retrieved from https://www.ijprt.org/index.php/pub/article/view/3403