PREDICTING THE ONSET OF DIABETES USING RNN RBFN: A ROBUST DEEP LEARNING MODEL FOR PRECISION IN HEALTHCARE

According to the International Diabetes Federation (IDF), diabetes is a chronic condition that is just one of the glaringly increasing global health issues of our day. Unprocessed diabetes can harm the kidneys, nerves, and heart and initiate eye illnesses like diabetic retinopathy. The healthcare cost of diabetes was 760.3 billion in 2019 and is projected to upsurge to 824.7 billion by 2030, according to IDF.

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Publication Details

Journal
Sylwan
Published
2025-01-01
DOI
https://doi.org/10.59879/viisl
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

PREDICTING THE ONSET OF DIABETES USING RNN RBFN: A ROBUST DEEP LEARNING MODEL FOR PRECISION IN HEALTHCARE

P. Vidhya Saraswathi, J.K. Kiruthika, B. Dhiyanesh, R. Sangeethapriya et al.
Sylwan
Artificial Intelligence in Healthcare
article

PREDICTING THE ONSET OF DIABETES USING RNN RBFN: A ROBUST DEEP LEARNING MODEL FOR PRECISION IN HEALTHCARE

P. Vidhya Saraswathi, J.K. Kiruthika, B. Dhiyanesh, R. Sangeethapriya, K Divya, S. Gomathi
article en

Abstract

According to the International Diabetes Federation (IDF), diabetes is a chronic condition that is just one of the glaringly increasing global health issues of our day. Unprocessed diabetes can harm the kidneys, nerves, and heart and initiate eye illnesses like diabetic retinopathy. The healthcare cost of diabetes was 760.3 billion in 2019 and is projected to upsurge to 824.7 billion by 2030, according to IDF.

Sylwan
Openalex Percentile: Top 92%
Artificial Intelligence in Healthcare
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PREDICTING THE ONSET OF DIABETES USING RNN RBFN: A ROBUST DEEP LEARNING MODEL FOR PRECISION IN HEALTHCARE — P. Vidhya Saraswathi, J.K. Kiruthika, et al. · Sylwan (2025) | TGRS Research Map | TGRS