DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
Abstract
Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-powered tools, in pursuit of improving accuracy and efficiency of this process. While the unique challenges presented by each modality and clinical task...
Paper Details
Title
DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
Published Date
Oct 2, 2020
Journal
Volume
10
Issue
1
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