In the recent years, deep learning models have addressed many problems in various fields. Meanwhile, technology development has spawned the big data in healthcare rapidly. Nowadays, application of deep learning to sol...In the recent years, deep learning models have addressed many problems in various fields. Meanwhile, technology development has spawned the big data in healthcare rapidly. Nowadays, application of deep learning to solve the problems in healthcare is a hot research direction. This paper introduces the application of deep learning in healthcare extensively. We focus on 7 application areas of deep learning, which are electronic health records （EHR）, electrocardiography （ECG）, electroencephalogram （EEG）, community healthcare, data from wearable devices, drug analysis and genomics analysis. The scope of this paper does not cover medical image processing since other researchers have already substantially reviewed it. In addition, we analyze the merits and drawbacks of the existing works, analyze the existing challenges, and discuss future trends.展开更多
基金supported by US National Science Foundation (Nos. DBI-1356669 and Ⅲ-1526012)
文摘In the recent years, deep learning models have addressed many problems in various fields. Meanwhile, technology development has spawned the big data in healthcare rapidly. Nowadays, application of deep learning to solve the problems in healthcare is a hot research direction. This paper introduces the application of deep learning in healthcare extensively. We focus on 7 application areas of deep learning, which are electronic health records （EHR）, electrocardiography （ECG）, electroencephalogram （EEG）, community healthcare, data from wearable devices, drug analysis and genomics analysis. The scope of this paper does not cover medical image processing since other researchers have already substantially reviewed it. In addition, we analyze the merits and drawbacks of the existing works, analyze the existing challenges, and discuss future trends.
