A SURVEY ON USE OF MACHINE LEARNING IN HEALTHCARE SECTOR

In today’s world, Healthcare is transforming through machine learning in ways that are improving patient outcomes, smooth medical procedures and optimal treatment. Methods such as reinforcement learning, unsupervised learning, deep learning and natural language processing allow machine learning of ML to be more accurate in diagnosis, to come up with individualized treatment plans, and to work with resource management. Applications that revolutionize how medical care is provided — from automating administrative work to enhancing medical imaging to early disease detection and personalized suggestions — are being facilitated using machine learning techniques.   However, there are many obstacles in applying machine learning to healthcare. Both to justify the use of technologies and to ensure that it is used responsibly and fairly, these issues are, for example, algorithmic bias, data privacy and security and legal limitations.   In summary, Machine learning capabilities can render healthcare sector more efficient more effective, and individualized to the patient, more so for patients around the world. With ML techniques, the healthcare domain can be expanded further in the future research with development.

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