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Theses

Extracting Clinical Event Timelines : Temporal Information Extraction and Coreference Resolution in Electronic Health Records

Abstract : Important information for public health is contained within Electronic Health Records (EHRs). The vast majority of clinical data available in these records takes the form of narratives written in natural language. Although free text is convenient to describe complex medical concepts, it is difficult to use for medical decision support, clinical research or statistical analysis.Among all the clinical aspects that are of interest in these records, the patient timeline is one of the most important. Being able to retrieve clinical timelines would allow for a better understanding of some clinical phenomena such as disease progression and longitudinal effects of medications. It would also allow to improve medical question answering and clinical outcome prediction systems. Accessing the clinical timeline is needed to evaluate the quality of the healthcare pathway by comparing it to clinical guidelines, and to highlight the steps of the pathway where specific care should be provided.In this thesis, we focus on building such timelines by addressing two related natural language processing topics which are temporal information extraction and clinical event coreference resolution.Our main contributions include a generic feature-based approach for temporal relation extraction that can be applied to documents written in English and in French. We devise a neural based approach for temporal information extraction which includes categorical features.We present a neural entity-based approach for coreference resolution in clinical narratives. We perform an empirical study to evaluate how categorical features and neural network components such as attention mechanisms and token character-level representations influence the performance of our coreference resolution approach.
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  • HAL Id : tel-01997223, version 1

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Julien Tourille. Extracting Clinical Event Timelines : Temporal Information Extraction and Coreference Resolution in Electronic Health Records. Document and Text Processing. Université Paris-Saclay, 2018. English. ⟨NNT : 2018SACLS603⟩. ⟨tel-01997223⟩

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