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Found 7 papers, 4 papers with code
Improving Extraction of Clinical Event Contextual Properties from Electronic Health Records: A Comparative Study
Electronic Health Records are large repositories of valuable clinical data, with a significant portion stored in unstructured text format.
Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study
Stroke is a leading cause of disability and death.
Validating transformers for redaction of text from electronic health records in real-world healthcare
Protecting patient privacy in healthcare records is a top priority, and redaction is a commonly used method for obscuring directly identifiable information in text.
Discharge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Models
Brief Hospital Course (BHC) summaries are succinct summaries of an entire hospital encounter, embedded within discharge summaries, written by senior clinicians responsible for the overall care of a patient.
Transformer-based out-of-distribution detection for clinically safe segmentation
We find all of these approaches are unsuitable for safe segmentation as they provide confidently wrong predictions when operating OOD.
MedGPT: Medical Concept Prediction from Clinical Narratives
The data available in Electronic Health Records (EHRs) provides the opportunity to transform care, and the best way to provide better care for one patient is through learning from the data available on all other patients.
Estimating Redundancy in Clinical Text
This work is a quantitative examination of information redundancy in EHR notes.
