Machine Learning in Healthcare: A Deep Dive into Classification, Limitations, Prospects, And Hurdles
Keywords:
Machine Learning; Healthcare; Supervised learning; Unsupervised machine learning ; Efficiency; Data; Treatment; Mobile health.
Abstract
Recently, a range of advanced techniques, such as artificial intelligence and machine learning, have been used to analyse health-related data. Machine learning applications are helping medical practitioners become more proficient in diagnosing and treating patients. Numerous academics have used medical data to find trends and diagnose illnesses. There aren't many papers in the literature right now that discuss using machine learning algorithms to increase the efficiency and accuracy of healthcare data. We investigated how well time series healthcare parameters for heart rate data transfer (accuracy and efficiency) may be enhanced using machine learning methods. We explored a number of machine learning techniques for use in healthcare applications in this research. Following a thorough introduction and analysis of supervised and unsupervised machine learning algorithms.
Published
2024-03-25
Section
Research Article
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