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Found 8 papers, 4 papers with code
Where’s the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data
The gold standard in clinical data capturing is achieved via “expert-review”, where clinicians can have a dialogue with a domain expert (reviewers) and ask them questions about data entry rules.
An Investigation of Evaluation Metrics for Automated Medical Note Generation
To study the correlation between the automatic metrics and manual judgments, we evaluate automatic notes/summaries by comparing the system and reference facts and computing the factual correctness, and the hallucination and omission rates for critical medical facts.
ICDBigBird: A Contextual Embedding Model for ICD Code Classification
The International Classification of Diseases (ICD) system is the international standard for classifying diseases and procedures during a healthcare encounter and is widely used for healthcare reporting and management purposes.
Cohort Characteristics and Factors Associated with Cannabis Use among Adolescents in Canada Using Pattern Discovery and Disentanglement Method
COMPASS is a longitudinal, prospective cohort study collecting data annually from students attending high school in jurisdictions across Canada.
LexSubCon: Integrating Knowledge from Lexical Resources into Contextual Embeddings for Lexical Substitution
Contextual word embedding models have achieved state-of-the-art results in the lexical substitution task by relying on contextual information extracted from the replaced word within the sentence.
UmlsBERT: Clinical Domain Knowledge Augmentation of Contextual Embeddings Using the Unified Medical Language System Metathesaurus
Contextual word embedding models, such as BioBERT and Bio_ClinicalBERT, have achieved state-of-the-art results in biomedical natural language processing tasks by focusing their pre-training process on domain-specific corpora.
Where's the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data
The gold standard in clinical data capturing is achieved via "expert-review", where clinicians can have a dialogue with a domain expert (reviewers) and ask them questions about data entry rules.
Record fusion: A learning approach
We use this feature vector alongwith the ground-truth information to learn a classifier for each of the attributes of the database.
