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Machine Learning for Diabetes and Blood Glucose Prediction
Paperback
Publisher Price: $22.99
Publisher: Barbosa
Published: Aug 26 2026
Pages: 134
Weight: 0.42
Height: 0.29 Width: 6.00 Depth: 9.00
Language: English
This book describes various ML techniques and DL algorithms used to apply in diabetes prediction.such as
NB, RF, SVM, DT, J48, Sequential Minimal Optimization (SMO), ANN (Artificial Neural Network), Multi-Layer
Perceptron (MLP), Recurrent Neural Network (RNN), CNN and LSTM. Although
deep research in diabetes mellitus has provided strong proficiency to classify data,
there is still much to be discovered by considering the patient's diet, medication,
activity, and biological, environmental, behavioral, and decision factors. Traditional
ML models are easy to interpret but achieve less predictive accuracy while ensemble
models provide higher accuracy. Existing studies proved that DL models performed
comparatively better on complex datasets than the ML models.
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