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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...
To improve their knowledge of diseases, physicians need to study and learn from their patients and from their related medical records. Physicians continue to initiate this learning process by taking into account the history of the patient’s medical problems and physical examination findings in the patient’s medical record, which illustrates the importance of medical and health care databases. In other...
Nowadays, patients are often in a hurry to know their analysis and concise explanations their medical images pending the doctor’s decision. Most of the time, doctors can make mistakes leading to unpredictable damage in patients. In order to minimize medical errors by fostering collaboration between physicians and/or patients, we propose in this paper, as a first contribution, a medical social network...
Collaborative environments in recent years, such as bioinformatics and health care, have seen an increasing interest in Web services communities. The new concept was proposed and widely accepted as a distributed paradigm over the Internet, and has been used widely even in collaborative fixture design and manufacture. Indeed, the community infrastructure contributes to improving the availability of...
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...
Thanks to the new positioning and information capture technologies; trajectory data which handle information related to moving objects can be captured and treated. This gave birth to a new data warehouse type called trajectory data warehouse that is essential to model and to implement to analyze and understand the nature and the behavior of movements of objects in various contexts. However, it is...
A medical report contains many elements such as medical images accompanied by text descriptions. We present in this paper a new approach for semantic automatic annotation of medical images. The proposed approach uses the bag of words model to represent the visual content of the medical image combined with text descriptors based on term frequency–inverse document frequency technique and reduced by...
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