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Found 7 papers, 4 papers with code
Simple Yet Powerful: An Overlooked Architecture for Nested Named Entity Recognition
Named Entity Recognition (NER) is an important task in Natural Language Processing that aims to identify text spans belonging to predefined categories.
Ranked #1 on
Nested Named Entity Recognition
on Chilean Waiting List
(Micro F1 (Exact Span) metric)
Automatic Extraction of Nested Entities in Clinical Referrals in Spanish
The annotated corpus, clinical word embeddings, annotation guidelines, and neural models are freely released to the community.
Clinical Flair: A Pre-Trained Language Model for Spanish Clinical Natural Language Processing
To validate the quality of the contextual representations retrieved from our model, we tested them on four named entity recognition datasets belonging to the clinical and biomedical domains.
Physics-informed neural networks for blood flow inverse problems
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available.
The Chilean Waiting List Corpus: a new resource for clinical Named Entity Recognition in Spanish
The best results were achieved by using a biLSTM-CRF architecture using word embeddings trained over Spanish Wikipedia together with clinical embeddings computed by the group.
PLN CMM at SocialDisNER: Improving Detection of Disease Mentions in Tweets by Using Document-Level Features
The proposed model is an architecture based on the FLERT approach.
Automatic Coding at Scale: Design and Deployment of a Nationwide System for Normalizing Referrals in the Chilean Public Healthcare System
This system could be a support tool for health professionals, optimizing the coding and management process.
