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With the exponential growth of medical data, Machine Learning (ML) algorithms are becoming increasingly important to the management and organization of healthcare information. This study aims to explore the role that ML can play in optimizing the management and organization of healthcare records, by identifying the challenges, advantages, and limitations associated with this technology. Consequently, the current study will contribute to the understanding of how ML might be applied to the healthcare industry in a variety of circumstances. Using the findings of this study, healthcare professionals, researchers, and policymakers will be able to make informed decisions regarding the adoption and implementation of ML techniques for regulating healthcare records. The findings of this paper revealed that ML can play an important role in efficiently directing and classifying healthcare records using different perspectives.
Alghamdi et al. (Tue,) studied this question.