Abstract
With the introduction of AI in health care, it became easier to identify diseases causing bacteria and viruses and to give expert advice for infectious diseases. The main idea behind applying machine learning for health care is the requirement of a robust algorithm to make a wise decision in life or death situation. Also, electronic health data adoption has increased almost ten times since 2009, and it paved the way for machine learning into health care. Machine learning made it possible to learn from unsupervised and semi-supervised data with high-dimensional features. Many leading industries started showing interest in healthcare and related products. Deep learning also enabled the early detection of deadly diseases which increased the lifespan of people. In this chapter, we will discuss how machine learning has rooted in health care and some of its valuable applications in health care.
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Kumawat, V., Umamaheswari, B., Mitra, P., Lavania, G. (2022). Machine Learning for Health Care: Challenges, Controversies, and Its Applications. In: Kumar, R., Ahn, C.W., Sharma, T.K., Verma, O.P., Agarwal, A. (eds) Soft Computing: Theories and Applications. Lecture Notes in Networks and Systems, vol 425. Springer, Singapore. https://doi.org/10.1007/978-981-19-0707-4_24
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