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January 1, 2026International Journal of Biomedical Engineering and Technology

MA-TIL-GBNN: A Multi-Attention Enhanced Deep Incremental Learning Based Diabetes Prediction and Drug Recommendation Framework

Netra Patil Naveenkumar Jayakumar Rohini Jadhav Gauri R. Rao Shashank Joshi Shubhangi R. Katkar Madhavi Mane

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Key Points

The research aims to develop a framework for predicting diabetes and recommending drugs using deep learning techniques.
Utilized a multi-attention deep learning approach
Implemented incremental learning to adapt to new data
Evaluated the framework's effectiveness in diabetes prediction and drug recommendation
Demonstrated improved prediction accuracy for diabetes
Showed relevant drug recommendations based on predictive analysis
Indicated the framework's ability to learn from new information

Implication

Framework predicts diabetes and recommends drugs using enhanced learning methods, indicating potential for improved healthcare.

Abstract

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Cite This Study

Patil et al. (2026) studied this question.

synapsesocial.com/papers/69d5f09e74eaea4b11a7a07b https://doi.org/10.1504/ijbet.2026.10077448

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