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KFU at CLEF eHealth 2017 Task 1: ICD-10 coding of English death certificates with recurrent neural networks

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dc.contributor.author Miftahutdinov Z.
dc.contributor.author Tutubalina E.
dc.date.accessioned 2018-04-05T07:09:55Z
dc.date.available 2018-04-05T07:09:55Z
dc.date.issued 2017
dc.identifier.issn 1613-0073
dc.identifier.uri http://dspace.kpfu.ru/xmlui/handle/net/130058
dc.description.abstract This paper describes the participation of the KFU team in the CLEF eHealth 2017 challenge. Specifically, we participated in Task 1, namely "Multilingual Information Extraction - ICD-10 coding" for which we implemented recurrent neural networks to automatically assign ICD-10 codes to fragments of death certificates written in English. Our system uses Long Short-Term Memory (LSTM) to map the input sequence into a vector representation, and then another LSTM to decode the target sequence from the vector. We initialize the input representations with word embeddings trained on user posts in social media. The encoderdecoder model obtained F-measure of 85.01% on a full test set with significant improvement as compared to the average score of 62.2% for all participants' approaches. We also obtained significant improvement from 26.1% to 44.33% on an external test set as compared to the average score of the submitted runs.
dc.relation.ispartofseries CEUR Workshop Proceedings
dc.subject Cepidc
dc.subject CLEF eHealth
dc.subject Death certificates
dc.subject Deep learning
dc.subject Encoder-decoder model
dc.subject Healthcare
dc.subject Icd-10 codes
dc.subject ICD-10 coding
dc.subject Machine learning
dc.subject Medical concept coding
dc.subject Recurrent neural network
dc.subject Sequence to sequence
dc.subject Sequence-to-sequence architecture
dc.title KFU at CLEF eHealth 2017 Task 1: ICD-10 coding of English death certificates with recurrent neural networks
dc.type Conference Paper
dc.relation.ispartofseries-volume 1866
dc.collection Публикации сотрудников КФУ
dc.source.id SCOPUS16130073-2017-1866-SID85034788154


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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