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Predicting cumulative effect of lifestyle risk factors for complex disease
In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient data generates personalized disease progression and predictions. However, the risk factors are fragmented all over medical literatu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160810/ https://www.ncbi.nlm.nih.gov/pubmed/35662748 http://dx.doi.org/10.1049/htl2.12021 |
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author | Effiok, Emmanuel Liu, Enjie Hitchcock, Jon |
author_facet | Effiok, Emmanuel Liu, Enjie Hitchcock, Jon |
author_sort | Effiok, Emmanuel |
collection | PubMed |
description | In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient data generates personalized disease progression and predictions. However, the risk factors are fragmented all over medical literature, certain risks can be accumulated for a disease and the aggregated probability may increase or decrease the occurrence of a disease. In this paper, a risk predictive framework which forms a base for a complete risk prediction model that can be used for various health applications is proposed. |
format | Online Article Text |
id | pubmed-9160810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91608102022-06-04 Predicting cumulative effect of lifestyle risk factors for complex disease Effiok, Emmanuel Liu, Enjie Hitchcock, Jon Healthc Technol Lett Original Research In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient data generates personalized disease progression and predictions. However, the risk factors are fragmented all over medical literature, certain risks can be accumulated for a disease and the aggregated probability may increase or decrease the occurrence of a disease. In this paper, a risk predictive framework which forms a base for a complete risk prediction model that can be used for various health applications is proposed. John Wiley and Sons Inc. 2022-03-17 /pmc/articles/PMC9160810/ /pubmed/35662748 http://dx.doi.org/10.1049/htl2.12021 Text en © 2022 The Authors. Healthcare Technology Letters published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Effiok, Emmanuel Liu, Enjie Hitchcock, Jon Predicting cumulative effect of lifestyle risk factors for complex disease |
title | Predicting cumulative effect of lifestyle risk factors for complex disease |
title_full | Predicting cumulative effect of lifestyle risk factors for complex disease |
title_fullStr | Predicting cumulative effect of lifestyle risk factors for complex disease |
title_full_unstemmed | Predicting cumulative effect of lifestyle risk factors for complex disease |
title_short | Predicting cumulative effect of lifestyle risk factors for complex disease |
title_sort | predicting cumulative effect of lifestyle risk factors for complex disease |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160810/ https://www.ncbi.nlm.nih.gov/pubmed/35662748 http://dx.doi.org/10.1049/htl2.12021 |
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