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Analysis of Link Prediction in Directed and Weighted Social Network Structure Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Breast Cancer Diagnosis and Prognosis Using Machine Learning Techniques

Authors : Sunil Suresh Shastri, Priyanka C. Nair, Deepa Gupta, Ravi C. Nayar, Raghavendra Rao, Amritanshu Ram

Published in: Intelligent Systems Technologies and Applications

Publisher: Springer International Publishing

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Abstract

Breast cancer is one of the major type of cancer which is the leading cause of death in women. The research work is carried out on the real data of patient records obtained from HealthCare Global Enterprises Ltd (HCG) hospitals. The work analyzes the four major class variables in the dataset, namely death, progression, recurrence and metastasis. The influence of the same 11 predictor variables is explored for each of the class. Various machine algorithms namely Support Vector Machine, Decision Tree, Multi-layer Perceptron and Naive Bayes have been explored for classification of the patient data into various classes. The imbalance in the data is handled using an over sampling technique. The contribution of various attributes in classifying the instances into different classes is also being explored. The model helps in predicting various factors and thus helps in early diagnosis in the breast cancer.

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Metadata
Title
Breast Cancer Diagnosis and Prognosis Using Machine Learning Techniques
Authors
Sunil Suresh Shastri
Priyanka C. Nair
Deepa Gupta
Ravi C. Nayar
Raghavendra Rao
Amritanshu Ram
Copyright Year
2018
Book
Intelligent Systems Technologies and Applications

Print ISBN: 978-3-319-68384-3

Electronic ISBN: 978-3-319-68385-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-68385-0_28

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