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Development of Machine Learning Models for Healthcare Systems Using Python: Machine Learning Models for COVID-19

Development of Machine Learning Models for Healthcare Systems Using Python: Machine Learning Models for COVID-19

Hemaraju Pollayi, Praveena Rao
Copyright: © 2022 |Pages: 30
ISBN13: 9781668437919|ISBN10: 1668437910|EISBN13: 9781668437926
DOI: 10.4018/978-1-6684-3791-9.ch007
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MLA

Pollayi, Hemaraju, and Praveena Rao. "Development of Machine Learning Models for Healthcare Systems Using Python: Machine Learning Models for COVID-19." Principles and Methods of Explainable Artificial Intelligence in Healthcare, edited by Victor Hugo C. de Albuquerque, et al., IGI Global, 2022, pp. 150-179. https://doi.org/10.4018/978-1-6684-3791-9.ch007

APA

Pollayi, H. & Rao, P. (2022). Development of Machine Learning Models for Healthcare Systems Using Python: Machine Learning Models for COVID-19. In V. Albuquerque, P. Srinivasu, A. Bhoi, & A. Briones (Eds.), Principles and Methods of Explainable Artificial Intelligence in Healthcare (pp. 150-179). IGI Global. https://doi.org/10.4018/978-1-6684-3791-9.ch007

Chicago

Pollayi, Hemaraju, and Praveena Rao. "Development of Machine Learning Models for Healthcare Systems Using Python: Machine Learning Models for COVID-19." In Principles and Methods of Explainable Artificial Intelligence in Healthcare, edited by Victor Hugo C. de Albuquerque, et al., 150-179. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-3791-9.ch007

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Abstract

Machine learning (ML) has been slowly entering every aspect of our lives, and its positive impact has been astonishing. To accelerate embedding ML in more applications and incorporating it in real-world scenarios, automated machine learning (AutoML) is emerging. The main purpose of AutoML is to provide seamless integration of ML in various industries, which will facilitate better outcomes in everyday tasks. After a violent disaster, the supply of medical services may fall short of the rising demand, leading to overcrowding in hospitals and, consequently, a collapse in the healthcare system. In the chapter, the authors created learning models for COVID-19 to understand how to design a proper ML workflow, which results in an organized, efficient product that produces desired results in terms of diagnosis, prediction, and recommendations. Large amounts of labeled training data are processed and analyzed to identify correlations, patterns, and make predictions using these patterns about future trends.

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