Diabetic Analysis and Prediction Using Deep Learning

Author:

Rao B. Narendra Kumar1,Poojitha Ambati2,Preethi Achyutha Guru2ORCID,Lalith Srinivas Aithepalli Suresh2,Reddy Buthuru Venkata Kiran Kumar2

Affiliation:

1. School of Computing, Mohan Babu University, Tirupati, India

2. Sree Vidyanikethan Engineering College, India

Abstract

Diabetes, a chronic metabolic disorder with wide-ranging health implications, presents a formidable global health challenge. Accurate prediction of the onset of diabetes is vital for tailoring effective preventive measures and enhancing patient outcomes. This study delves into the realm of deep learning methodologies to forecast the occurrence of diabetes in individuals. An expansive dataset, encompassing diverse individual profiles, lifestyle factors, and relevant medical parameters, will be employed to train a deep learning model. The research involves the creation of an innovative framework designed to unravel intricate patterns within the data, facilitating precise predictions of diabetes onset. The model leverages advanced neural network architectures to optimize feature extraction, capturing nuanced relationships critical for understanding the progression towards diabetes. This investigation contributes to the burgeoning field of medical artificial intelligence, highlighting the transformative potential of deep learning in redefining prognostic capabilities for diabetes.

Publisher

IGI Global

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