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Automatic blood glu...
Automatic blood glucose prediction with confidence using recurrent neural networks
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- Martinsson, John (författare)
- Chalmers University of Technology, Sweden,Chalmers tekniska högskola
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- Schliep, Alexander, 1967 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik, datavetenskap (GU),Department of Computer Science and Engineering, Computing Science (GU)
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- Eliasson, Björn (författare)
- Sahlgrenska University Hospital, Sweden,Sahlgrenska universitetssjukhuset
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- Meijner, Christian (författare)
- Chalmers University of Technology, Sweden,Chalmers tekniska högskola
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- Persson, Simon (författare)
- Chalmers University of Technology, Sweden,Chalmers tekniska högskola
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- Mogren, Olof (författare)
- RISE,SICS,RISE Research Institutes of Sweden
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(creator_code:org_t)
- CEUR, 2018
- 2018
- Engelska.
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Ingår i: CEUR Workshop Proceedings. - : CEUR. ; 2148, s. 64-68
- Relaterad länk:
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http://ceur-ws.org/V...
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https://urn.kb.se/re...
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https://research.cha...
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https://gup.ub.gu.se...
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Abstract
Ämnesord
Stäng
- Low-cost sensors continuously measuring blood glucose levels in intervals of a few minutes and mobile platforms combined with machine-learning (ML) solutions enable personalized precision health and disease management. ML solutions must be adapted to different sensor technologies, analysis tasks and individuals. This raises the issue of scale for creating such adapted ML solutions. We present an approach for predicting blood glucose levels for diabetics up to one hour into the future. The approach is based on recurrent neural networks trained in an end-to-end fashion, requiring nothing but the glucose level history for the patient. The model outputs the prediction along with an estimate of its certainty, helping users to interpret the predicted levels. The approach needs no feature engineering or data pre-processing, and is computationally inexpensive.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Nyckelord
- Blood
- Data handling
- Forecasting
- Glucose
- Health care
- Learning systems
- Blood glucose level
- Data preprocessing
- Disease management
- Feature engineerings
- Low-cost sensors
- Mobile platform
- Model outputs
- Sensor technologies
- Recurrent neural networks
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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