Clinical Text Classification to SNOMED CT Codes Using Transformers Trained on Linked Open Medical Ontologies.
Anton HristovPetar IvanovAnna AksenovaTsvetan AsamovPavlin GyurovTodor PrimovSvetla BoytchevaPublished in: RANLP (2023)
Keyphrases
- snomed ct
- text classification
- medical domain
- description logics
- medical diagnostic
- diagnostic imaging
- medical treatment
- patient records
- medical experts
- text mining
- medical data
- medical students
- medical knowledge
- medical records
- clinical decision support
- disease diagnosis
- medical diagnosis
- text categorization
- medical education
- diagnostic process
- medical information
- clinical practice
- therapy planning
- diabetic patients
- feature selection
- bag of words
- patient care
- clinical decision making
- medical center
- medical doctors
- medical imaging
- clinical data
- clinical guidelines
- machine learning
- medical databases
- medical practice
- national health
- health information systems
- traditional chinese medicine
- n gram
- training set
- intensive care
- multi label
- clinical decision support systems
- medical staff
- knowledge base
- semantic features
- patient data
- primary care
- hospital information systems
- heart disease
- patient groups
- home care
- health related
- ischemic stroke