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Clinical Concept Extraction
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Automatic extraction of clinical named entities such as clinical problems, treatments, tests and anatomical parts from clinical notes.
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
BURExtract-Llama: An LLM for Clinical Concept Extraction in Breast Ultrasound Reports
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records
CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain
Attention-based Clinical Note Summarization
Improving Clinical Document Understanding on COVID-19 Research with Spark NLP
NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction
CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters
Cost-effective Selection of Pretraining Data: A Case Study of Pretraining BERT on Social Media
Extracting clinical concepts from user queries
Clinical Concept Extraction: a Methodology Review
Clinical Concept Extraction for Document-Level Coding
Enhancing Clinical Concept Extraction with Contextual Embeddings
Clinical Concept Extraction with Contextual Word Embedding
CliNER 2.0: Accessible and Accurate Clinical Concept Extraction
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition
Bidirectional LSTM-CRF for Clinical Concept Extraction
Bidirectional LSTM-CRF for Clinical Concept Extraction
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