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This paper proposes a new approach of automatic medical image annotation since a social network whose users are student doctors in radiology in order to obtain report rapids on medical images. Indeed, the present study suggests a social network of collaboration where students or doctors can share their knowledge. Moreover, the annotations are used in order to extract the relevant keywords as well...
Medical social networking sites have enabled multimedia content sharing in large volumes by allowing physicians and patients to upload their medical images. Moreover, it is necessary to employ new techniques to effectively handle and benefit from them. This huge volume of images needs to formulate new types of queries that pose complex questions to medical social network databases. Content-based image...
Medical social networking sites enabled multimedia content sharing in large volumes, by allowing physicians and patients to upload their medical images. These images are diagnosed and commented, in different languages, by several specialists instantly. Moreover, it is necessary to employ new techniques, in order to automatically extract information and analyze knowledge from the huge number of comments...
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