Machine Learning and Medicine: The Interface of Medicine, Engineering and Artificial Intelligence by Simon W.Rabkin ISBN 9783725845644, 9783725845637, 3725845646, 3725845638 instant download

Machine Learning and Medicine: The Interface of Medicine, Engineering and Artificial Intelligence by Simon W.Rabkin ISBN 9783725845644, 9783725845637, 3725845646, 3725845638 instant download

Healthcare is an important industry which offers value-based care to millions of people while, at the same time, being a top revenue earner for many countries. Machine learning (ML) in healthcare, medical diagnosis, and treatment is one such area that is seeing gradual acceptance in the industry. Google recently developed a machine-learning algorithm to identify cancerous tumors in mammograms, and researchers at Stanford University are applying deep learning to detecting skin cancer. Machine learning has already been helpful in a variety of situations in healthcare. ML in healthcare helps to analyze thousands of different datapoints and suggest outcomes, provide timely risk scores, and has many other applications.
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Therefore, the increasingly growing number of applications of machine learning in healthcare allows us a glimpse into a future where data, analysis, and innovation work hand-in-hand to help countless patients. Soon, it will be quite common to find ML-based applications embedded with real-time patient data available from different healthcare systems in multiple countries, thereby increasing the efficacy of new treatment options that were previously unavailable.
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This particular collection aims to bring forward recent advances and present state-of-the-art developments in the theoretical and practical aspects of machine learning in healthcare. Since the emergence of deep-learning techniques and advanced computation technologies, many researchers of different backgrounds have contributed to this area, which has benefited from the heterogeneity and interdisciplinary of finding that are now well established.