Ai for autonomous health care on diabetes diagnostics

The project aims to improve diabetes prediction using Artificial Intelligence and Machine Learning (AIML) technologies. Diabetes is a chronic disease that needs to be detected early and monitored regularly. Conventional diagnostic methods are based on clinical evaluation and laboratory tests, which are time-consuming and expensive. The system uses cloud computing and machine learning algorithms to create a scalable and effective diabetes prediction model. With patient health data like glucose levels, BMI, age, and insulin levels, the system implements machine learning techniques like Logistic Regression, Random Forest, and Neural Networks to estimate the probability of diabetes. Integration with the cloud provides real-time analytics, data security, and easy access to healthcare professionals.

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Publication Details

Journal
South Health and Policy
Published
2025-04-07
DOI
https://doi.org/10.56294/shp2025236
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Ai for autonomous health care on diabetes diagnostics

Hari Kiran Vege, Sri Kamal Yandamuri, Jetti Vennela, Sai Venkat
South Health and Policy
Artificial Intelligence in Healthcare
article

Ai for autonomous health care on diabetes diagnostics

Hari Kiran Vege, Sri Kamal Yandamuri, Jetti Vennela, Sai Venkat
article en

Abstract

The project aims to improve diabetes prediction using Artificial Intelligence and Machine Learning (AIML) technologies. Diabetes is a chronic disease that needs to be detected early and monitored regularly. Conventional diagnostic methods are based on clinical evaluation and laboratory tests, which are time-consuming and expensive. The system uses cloud computing and machine learning algorithms to create a scalable and effective diabetes prediction model. With patient health data like glucose levels, BMI, age, and insulin levels, the system implements machine learning techniques like Logistic Regression, Random Forest, and Neural Networks to estimate the probability of diabetes. Integration with the cloud provides real-time analytics, data security, and easy access to healthcare professionals.

South Health and PolicyVol. 4
Koneru Lakshmaiah Education Foundation (IN)
Openalex Percentile: Top 88%
Artificial Intelligence in Healthcare
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