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Machine Learning Techniques and Breast Cancer Prediction: A Review

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Abstract

Cancer is one of the most prevalent diseases in humans, both in terms of incidence and fatality. Cancer care is a growing area of focus for developing interventions to improve the overall quality of life and longevity. Physical exercise has been continuously identified as a critical component of rehabilitation for a variety of chronic conditions and has been shown to improve first-class lifestyles and decrease all-cause mortality. Recent observational research suggests that moderate amounts of physical activity may also reduce the probability of dying from cancer, implying that exercise may be a beneficial strategy to improve not only exceptional but also standard survival. The classification of cancer modalities using machine learning modeling has been extensively discussed in this research work. This work helps contemporary and future researchers to build a foundation and conceptualize the technological factors involved in cancer research.

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  1. Nishtha Hooda and Nidhi Rani Gupta have contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science Engineering, Chandigarh University, Mohali, 140413, Punjab, India

    Gagandeep Kaur & Ruchika Gupta

  2. Department of Computer Science Engineering, IIIT, Una, 174303, Himachal Pradesh, India

    Nistha Hooda

  3. Department of Chemistry, Multani Mal Modi College, Patiala, 140201, Punjab, India

    Nidhi Rani Gupta

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  1. Gagandeep Kaur
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Kaur, G., Gupta, R., Hooda, N. et al. Machine Learning Techniques and Breast Cancer Prediction: A Review. Wireless Pers Commun 125, 2537–2564 (2022). https://doi.org/10.1007/s11277-022-09673-3

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