The World Health Organization defines Smart Healthcare as “Information and Communication Technology applications in the medical and health fields, including medical care, disease management, public health monitoring, education, and research.” In addition, many scholars believe that “Smart Healthcare” refers also to the integration of medical informatics, public health, and business applications mainly through the Internet and related artificial intelligence and data mining technologies in order to provide more accurate personal healthcare services and health information. The concept of deep learning has gained ground rapidly in recent years. While deep learning is usually applied to the studies of image/object recognition such as board game notations, paintings, people/things/objects in pictures, and so on, it is also often applied to the extraction of features. However, researchers have rarely used deep learning methods to predict outcomes in the medical and healthcare fields, preferring instead to make these predictions using algorithms based in traditional statistical methods and regression analysis. This paper introduces and investigates deep learning methods in the context of predicting outcomes in the medical and healthcare fields.
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