• AQSA FATIMA
• Haniya Jabeen
• Fatima Umaira Saeed

Diabetes mellitus, a chronic metabolic disorder characterized by elevated blood glucose levels, poses a significant global health burden. Timely and accurate diagnosis is crucial for effective management and prevention of complications. In recent years, artificial intelligence (AI) has emerged as a promising tool for improving the diagnostic process of diabetes. This review article provides an overview of the current state of AI applications in diagnosing diabetes, encompassing various methodologies such as machine learning, deep learning, and predictive modeling. We discuss the utilization of diverse data sources including medical images, electronic health records, genetic information, and lifestyle factors for diabetes diagnosis. Furthermore, we examine the performance, challenges, and potential future directions of AI-based diagnostic tools in clinical practice. By synthesizing existing literature and highlighting key advancements, this review aims to elucidate the role of AI in enhancing the accuracy and efficiency of diabetes diagnosis, ultimately contributing to improved patient outcomes and healthcare delivery.

Diabetes mellitus, Diagnosis, Artificial intelligence, Machine learning, Deep learning.

"ARTIFICIAL INTELLIGENCE IN DIABETES DIAGNOSIS : PIONEERING PRECISION HEALTHCARE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.k253-k263, April-2024, Available :http://www.jetir.org/papers/JETIR2404A33.pdf

"ARTIFICIAL INTELLIGENCE IN DIABETES DIAGNOSIS : PIONEERING PRECISION HEALTHCARE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppk253-k263, April-2024, Available at : http://www.jetir.org/papers/JETIR2404A33.pdf