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Found 4 papers, 1 papers with code
Improving Precancerous Case Characterization via Transformer-based Ensemble Learning
The application of natural language processing (NLP) to cancer pathology reports has been focused on detecting cancer cases, largely ignoring precancerous cases.
Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study
While the NLP system showed high precision and recall measurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance varied between individual sites.
Characterizing Design Patterns of EHR-Driven Phenotype Extraction Algorithms
Good classification accuracy with simple features demonstrated the attribution coherence and the feasibility of automatic identification of design patterns.
Developing a Portable Natural Language Processing Based Phenotyping System
Our system facilitates portable phenotyping of obesity and its 15 comorbidities based on the unstructured patient discharge summaries, while achieving a performance that often ranked among the top 10 of the challenge participants.
