A Call for Deep learning in Healthcare
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Abstract
The concept of personalising patient care has a long history, and current advancements in diagnostic medical imaging and molecular medicine are slowly but steadily revolutionising healthcare services by providing information and diagnostic tools that allow for tailored patient treatment. Multiple heterogeneous elements, such as socio-demographics, gene variability, environmental, and lifestyle factors, must be considered in order to facilitate personalized/precision treatment. As a result, one of the most pressing difficulties in personalised medicine is transforming enormous amounts of multimodal data into decision support tools capable of bridging the gap between research and clinical practise.Deep learning (DL) provides a unique answer to these issues, allowing for the acquisition or building of high-accuracy, multi-modal prediction models that will soon enable the realisation of the personalised medicine vision.
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