Abstract

Machine Learning, a form of Artificial Intelligence (AI) is infiltrating medical field and it is an era where machines can play an important role in health improvement. The idea behind AI in medical field is to enhance doctor's medical expertise. Medical Imaging is experiencing a drastic acceleration with rapid advancement in Machine Learning (ML) techniques. ML plays an important role in the medical imaging field including diagnosis, registration, segmentation and image database retrieval. ML can be applied to medical data repositories that are too large for the human brain to parse. ML promises to cut cost dramatically and deliver more accurate diagnosis than that of a trained physician. The patterns built from large clinical data warehouse can help researchers to draw conclusions and predict an event. This paper presents a comprehensive survey of the state-of-art work on Machine Learning in medical domain, which identifies the contributions of different methods, applications. In addition current issues and challenges are also discussed to identify promising areas of future research.

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