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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
Article Published : 8549
Total Authors : 22487
Total Reviewer : 811
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| Paper Title: | A Comprehensive Survey on Machine Learning and Deep Learning Techniques for Diabetes Prediction |
| Authors Name: | Vandana C , Hema B , Monika S , Sinchana T , Dr. Manjunath T K |
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IJRTI_203383
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| Published Paper Id: | IJRTI2505032 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Diabetes is among the most common chronic conditions globally, having a significant influence on global healthcare systems. Early and precise prediction of diabetes can help in early intervention and management. This paper is a detailed survey of current methods employed for diabetes prediction, with emphasis on a broad spectrum of machine learning (ML) and deep learning (DL) methods. The literature reviewed contains recent research studies that used algorithms like Random Forest, Support Vector Machine, Logistic Regression, Naïve Bayes, XGBoost, Artificial Neural Networks, Convolutional Neural Networks, ensemble learning models, and optimization-based methods. Metrics such as accuracy, AUC, RMSE, and MAE were taken into account for comparative assessment. The research shows that ensemble and hybrid models tend to perform better than single classifiers, with some models having a prediction accuracy of up to 100%. The paper also identifies new trends, including the use of sensor data, reinforcement learning, and explainable AI for predicting diabetes. In summary, this survey gives a systematic reference for researchers and practitioners seeking to develop precise, trustworthy, and scalable solutions for diabetes monitoring and diagnosis. |
| Keywords: | Diabetes Prediction, Machine Learning, Deep Learning, Artificial Intelligence, Medical Diagnosis, Healthcare Analytics, Classification Algorithms, Disease Prediction, Ensemble Models, Neural Networks |
| Cite Article: | "A Comprehensive Survey on Machine Learning and Deep Learning Techniques for Diabetes Prediction", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a328-a337, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505032.pdf |
| Downloads: | 000491 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505032
Registration ID:203383
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a328-a337 Country: Bengaluru, Karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505032 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505032 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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