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Like other real-world problems, reasoning in clinical depression presents cognitive challenges for clinicians. This is due to the presence of co-occuring diseases, incomplete data, uncertain knowledge, and the vast amount of data to be analysed. Current approaches rely heavily on the experience, knowledge, and subjective opinions of clinicians, creating scalability issues. Automating this process...
Depression is a serious worldwide public health problem, and its diagnosis still remains a challenge in the medical community. The difficulties of detecting depression are largely due to its high comorbid factor. Given the reciprocal relationship between depression and physical illness, mental health professionals have called for a diagnostic approach that identifies and evaluates each disorder, concurrently...
Recording university lectures through lecture capture systems is increasingly common, generating large amounts of audio and video data. Transcribing recordings greatly enhances their usefulness by making them easy to search. However, the number of recordings accumulates rapidly, rendering manual transcription impractical. Automatic transcription, on the other hand, suffers from low levels of accuracy,...
A wireless sensor network (WSN)consisting of a large number of tiny sensors can be an effective tool for gathering data in diverse kinds of environments. The data collected by each sensor is communicated to the base station, which forwards the data to the end user. Clustering is introduced to WSNs because it has proven to be an effective approach to provide better data aggregation and scalability...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.