Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Prediction of Female Diabetic Patient in India Using Different Learning Algorithms

Version 1 : Received: 3 June 2021 / Approved: 4 June 2021 / Online: 4 June 2021 (15:25:16 CEST)

How to cite: Bandyopadhyay, S.; Bose, P.; Goyel, V. Prediction of Female Diabetic Patient in India Using Different Learning Algorithms. Preprints 2021, 2021060144 (doi: 10.20944/preprints202106.0144.v1). Bandyopadhyay, S.; Bose, P.; Goyel, V. Prediction of Female Diabetic Patient in India Using Different Learning Algorithms. Preprints 2021, 2021060144 (doi: 10.20944/preprints202106.0144.v1).

Abstract

Diabetics or Diabetic Mellitus is a metabolic disorder of blood sugar levels in the human body. It is a major non-communicable disease and involved many serious health risk issues. This disease is rapidly increasing in India. It is a chronic condition and it occurs when a body doesn't produce enough insulin hormone to control the blood sugar level. In this study, different variables have been analyzed that cause the diabetics, and different machine learning algorithms are used to predict whether an unknown sample is diabetes or not. For this purpose, PIMA diabetic detection for Female patients was used. Here 10 different classification model is used for prediction. Finally, the detailed performance analysis of the different variables of the PIMA dataset and also the classification model are discussed.

Subject Areas

Diabetic; Diabetic Mellitus; Diabetic Prediction; PIMA diabetic dataset; Female diabetic Patients; Machine Learning

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.