Abstract
The healthcare providers use clinical decision support systems to manage the patients’ electronic health records. In this paper, we aim to enhance the computer-aided diagnosis in medical imaging. We developed a graph-based tag recommendations approach that suggests relevant diseases and pathologies by analysing the tagged medical images. Healthcare providers can rapidly get an improved diagnostic value of radiographs using the graph-based tag recommendations that enable discovering common and relevant diseases used within the patient’s community, his related images and semantically tied tags. The dataset ChestX-Ray14 has been conducted to evaluate the accuracy and effectiveness of our proposal. Futures works will address the online evaluation of the suggested tags by exploiting the healthcare providers’ feedback.
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Qassimi, S., Abdelwahed, E.H., Hafidi, M., Lamrani, R. (2018). A Graph-Based Model for Tag Recommendations in Clinical Decision Support System. In: Abdelwahed, E., Bellatreche, L., Golfarelli, M., Méry, D., Ordonez, C. (eds) Model and Data Engineering. MEDI 2018. Lecture Notes in Computer Science(), vol 11163. Springer, Cham. https://doi.org/10.1007/978-3-030-00856-7_19
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DOI: https://doi.org/10.1007/978-3-030-00856-7_19
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