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Machine Learning in Healthcare

Machine Learning in Healthcare

Debasree Mitra, Apurba Paul, Sumanta Chatterjee
Copyright: © 2021 |Pages: 24
ISBN13: 9781799830924|ISBN10: 1799830926|EISBN13: 9781799830931
DOI: 10.4018/978-1-7998-3092-4.ch002
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MLA

Mitra, Debasree, et al. "Machine Learning in Healthcare." AI Innovation in Medical Imaging Diagnostics, edited by Kalaivani Anbarasan, IGI Global, 2021, pp. 37-60. https://doi.org/10.4018/978-1-7998-3092-4.ch002

APA

Mitra, D., Paul, A., & Chatterjee, S. (2021). Machine Learning in Healthcare. In K. Anbarasan (Ed.), AI Innovation in Medical Imaging Diagnostics (pp. 37-60). IGI Global. https://doi.org/10.4018/978-1-7998-3092-4.ch002

Chicago

Mitra, Debasree, Apurba Paul, and Sumanta Chatterjee. "Machine Learning in Healthcare." In AI Innovation in Medical Imaging Diagnostics, edited by Kalaivani Anbarasan, 37-60. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-3092-4.ch002

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Abstract

Machine learning is a popular approach in the field of healthcare. Healthcare is an important industry that provides service to millions of people and as well as at the same time becoming top revenue earners in many countries. Machine learning in healthcare helps to analyze thousands of different data points and suggest outcomes, provide timely risk factors, optimize resource allocation. Machine learning is playing a critical role in patient care, billing processing to set the target to marketing and sales team, and medical records for patient monitoring and readmission, etc. Machine learning is allowing healthcare specialists to develop alternate staffing models, intellectual property management, and using the most effective way to capitalize on developed intellectual property assets. Machine learning approaches provide smart healthcare and reduce administrative and supply costs. Today healthcare industry is committed to deliver quality, value, and satisfactory outcomes.

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