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LIMSI-COT at SemEval-2017 Task 12: Neural Architecture for Temporal Information Extraction from Clinical Narratives
2017
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
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In this paper we present our participation to SemEval 2017 Task 12. ...
We used a neural network based approach for entity and temporal relation extraction, and experimented with two domain adaptation strategies. We achieved competitive performance for both tasks. ...
Acknowledgements This work was supported by Labex Digicosme, operated by the Foundation for Scientific Cooperation (FSC) Paris-Saclay, under grant CÔT. ...
doi:10.18653/v1/s17-2098
dblp:conf/semeval/TourilleFTN17
fatcat:rrfd7htejjfo3llwz6ar7litue
Reconstructing the Patient's Natural History from Electronic Health Records
2020
Zenodo
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
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Any intelligent system should then be able to extract medical concepts, date expressions, temporal relations and the temporal ordering of medical events from the free texts of EHRs; yet, this task is hard ...
The automatic extraction of a patient's natural history from Electronic Health Records (EHRs) is a critical step towards building intelligent systems that can reason about clinical variables and support ...
precision medicine and suggested treatments for different types of patients); MN is also supported by UPM (Universidad Politécnica de Madrid) Programa Propio of PhD grants. ...
doi:10.5281/zenodo.3765826
fatcat:ir32plqjzfawhpach7cpzvsa7e