Combining supervised and unsupervised named entity recognition to detect psychosocial risk factors in occupational health checks.
Leena UronenSanna SalanteräKai HakalaJaakko HartialaHans MoenPublished in: Int. J. Medical Informatics (2022)
Keyphrases
- named entity recognition
- risk factors
- semi supervised
- cardiovascular disease
- unsupervised learning
- high risk
- supervised learning
- named entities
- sequence labeling
- information extraction
- risk assessment
- text summarization
- risk management
- relation extraction
- natural language processing
- maximum entropy
- weakly supervised
- active learning
- pairwise
- conditional random fields
- annotated corpus
- pos taggers
- diabetes mellitus
- generative model
- statistical methods
- classifier ensemble
- machine learning
- learning algorithm
- health care
- object recognition
- statistical model
- image segmentation
- decision trees
- feature selection
- artificial intelligence
- information retrieval
- data mining
- maximum entropy classifier