A considerable amount of medically relevant information is hidden in large unstructured heterogeneous data collections, such as the medical literature, medicinal patents, electronic health records or specialized web-content (health blogs, patient forums or information generated by scientific and medical societies). To process more efficiently medical big data there is a growing interest in exploiting natural language processing and text mining approaches, in particularly deep learning and artificial intelligence-based strategies.
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