February 13, 2025

Advances in Type II Diabetes Prediction: A Comprehensive Review of Machine Learning Techniques

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Why the study?

Type II diabetes mellitus is a growing global concern, raising the need for accurate forecasts beyond traditional methods.

Do machine learning algorithms improve the prediction of Type II diabetes compared to traditional methods?

Design

Comprehensive review

Authors

VKVirendra Singh KushwahMadhya Pradesh Bhoj Open University SKSivaneasan Bala KrishnanSingapore Institute of Technology KUKamal UpretiInstitute of Management Technology

Discussion

Member takes

Overview

ML may aid T2D prediction; leaves open clinical translation pending interpretability and validation.

Structured PICO

Do machine learning algorithms improve the prediction of Type II diabetes compared to traditional methods?

Population

Populations at risk for Type II diabetes

Intervention

Machine learning algorithms (including logistic regression, random forest, support vector regression, ensemble learning, deep learning, and hybrid methods)

Comparator

Traditional prediction methods

Outcome

Prediction of Type II diabetes risk

Machine learning techniques offer enhanced predictive capabilities for Type II diabetes risk, though challenges in interpretability and clinical implementation remain.

Cite This Study

Kushwah et al. (2025) studied this question.

synapsesocial.com/papers/6a0faee42badbc352afe8a9c https://doi.org/10.1109/ic363308.2025.10956963

Topics

Artificial intelligence in cardiology

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February 13, 2025

Advances in Type II Diabetes Prediction: A Comprehensive Review of Machine Learning Techniques

View Full Paper

Ask AI

Bookmark

Why the study?

Type II diabetes mellitus is a growing global concern, raising the need for accurate forecasts beyond traditional methods.

Do machine learning algorithms improve the prediction of Type II diabetes compared to traditional methods?

Design

Comprehensive review

Authors

VKVirendra Singh KushwahMadhya Pradesh Bhoj Open University SKSivaneasan Bala KrishnanSingapore Institute of Technology KUKamal UpretiInstitute of Management Technology

Discussion

Member takes

Overview

ML may aid T2D prediction; leaves open clinical translation pending interpretability and validation.

Structured PICO

Do machine learning algorithms improve the prediction of Type II diabetes compared to traditional methods?

Population

Populations at risk for Type II diabetes

Intervention

Machine learning algorithms (including logistic regression, random forest, support vector regression, ensemble learning, deep learning, and hybrid methods)

Comparator

Traditional prediction methods

Outcome

Prediction of Type II diabetes risk

Machine learning techniques offer enhanced predictive capabilities for Type II diabetes risk, though challenges in interpretability and clinical implementation remain.

Cite This Study

Kushwah et al. (2025) studied this question.

synapsesocial.com/papers/6a0faee42badbc352afe8a9c https://doi.org/10.1109/ic363308.2025.10956963

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

Topics

Artificial intelligence in cardiology

View Full Paper

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