Search Results for author:
Found 10 papers, 4 papers with code
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.
Challenges and Opportunities of Using Transformer-Based Multi-Task Learning in NLP Through ML Lifecycle: A Survey
The increasing adoption of natural language processing (NLP) models across industries has led to practitioners' need for machine learning systems to handle these models efficiently, from training to serving them in production.
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
We explore how temporal modelling of patients from free text and structured data, using deep generative transformers can be used to forecast a wide range of future disorders, substances, procedures or findings.
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.
