Overview of the ShARe/CLEF eHealth Evaluation Lab 2014
By Liadh Kelly, Lorraine Goeuriot, H. Suominen, Tobias Schreck, Gondy Leroy, Danielle L. Mowery, Sumithra Velupillai, Wendy W. Chapman, David Martínez, Guido Zuccon and 1 more. Conference and Labs of the Evaluation Forum, 2014
319 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/74b16ff4f72c8029ec3bafdb3bffff894cf9b038
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Citations in the corpus
- Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets (2019, background): “…training and test sets in the ChemProt shared task and evaluate the same five classes: CPR:3, CPR:4, CPR:5, CPR:6, and CPR:9. i2b2 2010 shared task collection consists of 170 documents for training and 256 documents for testing, which is the subset of the original dataset (Uzuner et al., 2011).”
- Clinical Text Data in Machine Learning: Systematic Review (2020, background): “[54,57,88,98,114] Disorders, acronyms, and abbreviations 300 Discharge summaries, electrocardiogram reports, echocardiogram reports, radiology reports BIDMC 2013 ShARe/CLEF eHealth [126]”
- Enhancing Clinical Concept Extraction with Contextual Embedding (2019, background): “Concept extraction is the most common clinical natural language processing (NLP) task (Tang et al., 2013; Kundeti et al., 2016; Unanue et al., 2017; Wang et al., 2018b), and a precursor to downstream tasks such as relations (Rink et al., 2011), frames (Gupta et al., 2018; Si and Roberts, 2018),…”
- Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network (2015, background): “More recently, a number of challenges on NER involving shared tasks in clinical text have been organized, including the 2009 i2b2 (the Center of Informatics for Integrating Biology and the Bedside) challenge [7] on medication recognition, the 2010 i2b2 challenge [8] on recognizing medical problems, ”