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2021 | OriginalPaper | Chapter

Homo Sapiens Diabetes Mellitus Detection and Classification

Authors : Anu Agarwal, Anjay Sahoo, Indrashis Das, Siddharth S. Rautaray, Manjusha Pandey

Published in: Evolutionary Computing and Mobile Sustainable Networks

Publisher: Springer Singapore

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Abstract

Diabetes mellitus can be defined as a set of deficiency disorders which is caused due to under-secretion of insulin. In other words, it results in very high blood sugar levels. Diabetes mellitus influences and is influenced by various factors. Diabetes mellitus, if remains unidentified or untreated can lead to lethal disorders like a cardiovascular disease such as heart attack, narrowing of arteries, nerve damage, kidney damage, skin conditions, depression, and many such complications. Statistics suggest that human beings are getting affected by this disease at an alarming rate. Yet, it remains unidentified and hence untreated in most cases. Hence, machine learning is introduced in the field of biomedical sciences such that these disorders can be treated at a larger scale without conducting pathological tests. The below paper solely focuses on predicting over a set of features for every human that if the person has a tendency of high blood sugar or diabetes mellitus or not. Building the classifier includes libraries like Python, Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn, and Scipy.

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Metadata
Title
Homo Sapiens Diabetes Mellitus Detection and Classification
Authors
Anu Agarwal
Anjay Sahoo
Indrashis Das
Siddharth S. Rautaray
Manjusha Pandey
Copyright Year
2021
Publisher
Springer Singapore
Book
Evolutionary Computing and Mobile Sustainable Networks

Print ISBN: 978-981-15-5257-1

Electronic ISBN: 978-981-15-5258-8

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5258-8_42