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Predicting disease onset from electronic health records for population health management: a scalable and explainable Deep Learning approach.

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Title: Predicting disease onset from electronic health records for population health management: a scalable and explainable Deep Learning approach.
Authors: Grout R; Accenture, Leeds, United Kingdom., Gupta R; Accenture, San Francisco, CA, United States., Bryant R; Accenture, London, United Kingdom., Elmahgoub MA; Accenture, London, United Kingdom., Li Y; Accenture, London, United Kingdom., Irfanullah K; Accenture, London, United Kingdom., Patel RF; Accenture, London, United Kingdom., Fawkes J; Department of Statistics, University of Oxford, Oxford, United Kingdom., Inness C; Accenture, London, United Kingdom.
Source: Frontiers in artificial intelligence [Front Artif Intell] 2024 Jan 08; Vol. 6, pp. 1287541. Date of Electronic Publication: 2024 Jan 08 (Print Publication: 2023).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101770551 Publication Model: eCollection Cited Medium: Internet ISSN: 2624-8212 (Electronic) Linking ISSN: 26248212 NLM ISO Abbreviation: Front Artif Intell Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Media+SA%22">Frontiers Media SA </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101770551 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2624-8212 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2226248212%22">26248212 </searchLink><i>NLM ISO Abbreviation: </i>Front Artif Intell <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.3389/frai.2023.1287541
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              Text: 2024 Jan 08
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