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Found 5 papers, 1 papers with code
Clinical Named Entity Recognition using Contextualized Token Representations
To facilitate various downstream applications using clinical case reports (CCRs), we pre-train two deep contextualized language models, Clinical Embeddings from Language Model (C-ELMo) and Clinical Contextual String Embeddings (C-Flair) using the clinical-related corpus from the PubMed Central.
CREATe: Clinical Report Extraction and Annotation Technology
Clinical case reports are written descriptions of the unique aspects of a particular clinical case, playing an essential role in sharing clinical experiences about atypical disease phenotypes and new therapies.
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference
There has been a steady need in the medical community to precisely extract the temporal relations between clinical events.
EVIDENCEMINER: Textual Evidence Discovery for Life Sciences
EVIDENCEMINER is constructed in a completely automated way without any human effort for training data annotation.
