Retrofitting Word Embeddings with the UMLS Metathesaurus for Clinical Information Extraction.
Mohammed M. AlawadS. M. Shamimul HasanJames Blair ChristianGeorgia D. TourassiPublished in: IEEE BigData (2018)
Keyphrases
- umls metathesaurus
- information extraction
- natural language text
- word sense disambiguation
- free text
- machine learning
- natural language processing
- text mining
- named entities
- precision and recall
- clinical practice
- medical records
- co occurrence
- medical domain
- clinical guidelines
- information retrieval
- vector space
- named entity recognition
- word recognition
- n gram
- web mining
- relational learning
- web documents
- manifold learning
- patient data
- text documents
- clinical setting
- low dimensional
- clinical applications
- structured data
- natural language
- conditional random fields
- semi structured
- hidden markov models
- machine translation
- file system
- patient records
- text corpus
- medical data
- euclidean space
- ontology based information extraction
- high dimensional
- domain specific
- clinically relevant
- question answering
- speech recognition
- data mining
- word pairs
- text processing
- medical knowledge
- sentence level
- clinical data
- noun phrases
- relation extraction
- clinical trials