Key result
Diverse data mining techniques and machine learning algorithms were applied to an enriched Pima Indian Diabetes dataset to evaluate their efficacy in diabetes prediction.
Integration of wearable technology data with traditional datasets using machine learning can facilitate diabetes risk prediction and public health awareness.
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ML models may aid diabetes prediction on enriched datasets; hypothesis-generating and requires prospective validation before clinical use.
IJSREM Journal (2024) studied Diabetes. Data mining techniques (logistic regression, random forest, SVM, naive Bayes, neural networks) was evaluated on Diabetes prediction efficacy. Diverse data mining techniques and machine learning algorithms were applied to an enriched Pima Indian Diabetes dataset to evaluate their efficacy in diabetes prediction.
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