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Optimized Predictive Models in Health Care Using Machine Learning
book

Optimized Predictive Models in Health Care Using Machine Learning

by Sandeep Kumar, Anuj Sharma, Navneet Kaur, Lokesh Pawar, Rohit Bajaj
March 2024
Intermediate to advanced content levelIntermediate to advanced
384 pages
9h 52m
English
Wiley-Scrivener
Content preview from Optimized Predictive Models in Health Care Using Machine Learning

8A Robust Machine Learning Model for Breast Cancer Prediction

Rachna1, Chahil Choudhary2* and Jatin Thakur2

1Gateway Institute of Engineering and Technology (Sonipat), Haryana, India

2Dept. of Computer Science and Engineering, Chandigarh University, Mohali Punjab, India

Abstract

Breast cancer is a common form of cancer that can afflict people of any gender and develops when cells in the breast tissue grow malignantly. Breast cancer symptoms might include a lump in the breast and modifications to the breast’s size, shape, or texture. Age, family history, and genetic abnormalities are a few things that might make someone more likely to have breast cancer. Treatment options for breast cancer can vary depending on the stage and severity of cancer, but common approaches include surgery, radiation therapy, chemotherapy, and hormone therapy. Early detection through regular screenings, such as mammograms, can improve treatment outcomes. A recommended model utilizes a combination of feature selection, feature extraction, and ensemble learning techniques to effectively analyze patient information and make accurate predictions regarding breast cancer. Although feature extraction tries to minimize the dimensionality of the data and enhance model performance, feature selection is used to pinpoint the most pertinent aspects for the model to concentrate on. The precision of the model’s predictions is also increased by using ensemble learning strategies like bagging. Classification algorithms ...

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Publisher Resources

ISBN: 9781394174621Purchase Link