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A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning

Amirahmadi, Ali, 1994- (author)
Högskolan i Halmstad,Halmstad University,Akademin för informationsteknologi
Ohlsson, Mattias (author)
Högskolan i Halmstad,Halmstad University,Lund University,Lunds universitet,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,LU profilområde: Naturlig och artificiell kognition,Lunds universitets profilområden,Centre for Environmental and Climate Science (CEC),Faculty of Science,LU Profile Area: Natural and Artificial Cognition,Lund University Profile areas,Akademin för informationsteknologi,Lund University, Lund, Sweden
Etminani, Kobra, 1984- (author)
Högskolan i Halmstad,Halmstad University,Akademin för informationsteknologi
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Melander, Olle (author)
Lund University,Lunds universitet,Avdelningen för arbets- och miljömedicin,Institutionen för laboratoriemedicin,Medicinska fakulteten,Division of Occupational and Environmental Medicine, Lund University,Department of Laboratory Medicine,Faculty of Medicine,Lund University, Lund, Sweden
Björk, Jonas (author)
Lund University,Lunds universitet,Avdelningen för arbets- och miljömedicin,Institutionen för laboratoriemedicin,Medicinska fakulteten,Kirurgi och folkhälsa,Forskargrupper vid Lunds universitet,EPI@LUND,Division of Occupational and Environmental Medicine, Lund University,Department of Laboratory Medicine,Faculty of Medicine,Surgery and public health,Lund University Research Groups,Lund University, Lund, Sweden
Hagglund, Maria (editor)
Blusi, Madeleine (editor)
Bonacina, Stefano (editor)
Nilsson, Lina (editor)
Madsen, Inge Cort (editor)
Pelayo, Sylvia (editor)
Moen, Anne (editor)
Benis, Arriel (editor)
Lindskold, Lars (editor)
Gallos, Parisis (editor)
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 (creator_code:org_t)
Amsterdam : IOS Press, 2023
2023
English 2 s.
In: Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. - Amsterdam : IOS Press. - 1879-8365 .- 0926-9630. - 9781643683881 ; 302, s. 609-610, s. 609-610
Related links:
http://dx.doi.org/10... (free)
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https://doi.org/10.3...
https://lup.lub.lu.s...
https://doi.org/10.3...
https://urn.kb.se/re...
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  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effectively addressed the first challenge. Here we tackled the latter challenge by masking one source (e.g., ICD10 codes) and training the transformer to predict it using other sources (e.g., ATC codes).

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

deep learning
disease prediction
electronic health records
Masked language model
patient trajectories
representation learning
deep learning
Information driven care

Publication and Content Type

kon (subject category)
ref (subject category)

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