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Found 7 papers, 2 papers with code
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.
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data
The ability to perform accurate prognosis of patients is crucial for proactive clinical decision making, informed resource management and personalised care.
Multi-domain Clinical Natural Language Processing with MedCAT: the Medical Concept Annotation Toolkit
Electronic health records (EHR) contain large volumes of unstructured text, requiring the application of Information Extraction (IE) technologies to enable clinical analysis.
Comparative Analysis of Text Classification Approaches in Electronic Health Records
Text classification tasks which aim at harvesting and/or organizing information from electronic health records are pivotal to support clinical and translational research.
Identifying physical health comorbidities in a cohort of individuals with severe mental illness: An application of SemEHR
Multimorbidity research in mental health services requires data from physical health conditions which is traditionally limited in mental health care electronic health records.
MedCAT -- Medical Concept Annotation Tool
To uncover the potential of biomedical documents we need to extract and structure the information they contain.
MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation
Secondary use of data for clinical research often has task and context specific criteria.
