New system to automatically extract adverse drug reactions f

New system to automatically extract adverse drug reactions from electronic health records


New system to automatically extract adverse drug reactions from electronic health records
Researchers from the IXA group at the UPV/EHU are collaborating with Osakidetza (the Basque Regional Health Service) to create a system for automatically extracting adverse drug reactions from electronic health records written in Spanish. The researchers have conducted different tests using both machine learning and deep learning, with the aim of building a robust model for extracting relations between drug-disease pairs based on clinical text mining.
Patients' electronic health records convey crucial information. The application of natural language processing techniques to these records may be an effective means of extracting information that may improve clinical decision making, clinical documentation and billing, disease prediction and the detection of adverse drug reactions. Adverse drug reactions are a major health problem, resulting in hospital re-admissions and even the death of thousands of patients. An automatic detection system can highlight said reactions in a document, summarize them and automatically report them.

Related Keywords

Spain , Spanish , Sara Santiso , Emily Henderson , Basurto University Hospital , Osakidetza The Basque Regional Health Service , Basque Regional Health Service , Galdakao Hospital , Deep Learning , Hospital , Language , Machine Learning , Research , ஸ்பெயின் , ஸ்பானிஷ் , எமிலி ஹென்டர்சன் , பசியூ பிராந்திய ஆரோக்கியம் சேவை , ஆழமான கற்றல் , மருத்துவமனை , மொழி , இயந்திரம் கற்றல் , ஆராய்ச்சி ,

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