DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
نویسندگان
چکیده
منابع مشابه
Scalable and accurate deep learning for electronic health records
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a laborintensive process that discards the vast majority of information in each patient’s record. We propose a representation of...
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The recent years have witnessed a surge of interests in data analytics with patient Electronic Health Records (EHR). Data-driven healthcare, which aims at effective utilization of big medical data, representing the collective learning in treating hundreds of millions of patients, to provide the best and most personalized care, is believed to be one of the most promising directions for transform...
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We present a hypnogram generator fully written in Matlab/Octave programming languages. Our software extracts data from brainwaves during sleep and then classifies wave stretches according to their predominant frequency. Differently from other programs, which rely on heavily numerical data analyses, our approach is the plain shape analysis of the waves. For this purpose we focus on properties of...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2020
ISSN: 2045-2322
DOI: 10.1038/s41598-020-73126-9