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Artificial Intelligent Techniques for Wireless Communication and Networking
book

Artificial Intelligent Techniques for Wireless Communication and Networking

by R. Kanthavel, K. Anathajothi, S. Balamurugan, R. Karthik Ganesh
March 2022
Intermediate to advanced content levelIntermediate to advanced
384 pages
9h 32m
English
Wiley-Scrivener
Content preview from Artificial Intelligent Techniques for Wireless Communication and Networking

15Hereditary Factor-Based Multi-Featured Algorithm for Early Diabetes Detection Using Machine Learning

S. Deepajothi1, R. Juliana2, S.K. Aruna3 and R. Thiagarajan4*

1Dept. of CSE, Gurunanak Institute of Technology, Hyderabad, India

2Dept. of IT, Loyola ICAM College of Engineering & Technology, Chennai, India

3Dept. of CSE, Christ (Deemed to be University) School of Engineering & Technology, Bangalore, India

4Dept. of CSE, Prathyusha Engineering College, Thiruvallur, India

Abstract

Today’s advent in the medical industry have given numerous chances to improve the quality of detection and reporting the diseases at the early stages for a better diagnosis. Modern day datasets generate fruitful information for timely and periodic monitoring of patients’ health conditions. Such information is hidden to a naked eye or hidden in multiple track records of highly affected population. Diabetes mellitus is one such disease which is predominant among a global population which ultimately leads to blindness and death in some cases. The model proposed in this system attempts to design and deliver an intelligent solution for predicting diabetes in the early stages and address the problem of late detection and diagnosis. Intensive research is carried out in many tropical countries for automating this process through a machine learning model. The accuracy of machine learning algorithms is more than satisfactory in the detection of Type 2 diabetes from the dataset of PIMA Indians Diabetes Dataset. ...

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Publisher Resources

ISBN: 9781119821274Purchase Link