Predictive analytics in health care: how can we know it works?
There is increasing awareness that the methodology and findings of research should be transparent. This includes studies using artificial intelligence to develop predictive algorithms that make individualized diagnostic or prognostic risk predictions. We argue that it is paramount to make the algori...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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Oxford University Press
2019
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| _version_ | 1826297400152555520 |
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| author | Van Calster, B Wynants, L Timmerman, D Steyerberg, E Collins, G |
| author_facet | Van Calster, B Wynants, L Timmerman, D Steyerberg, E Collins, G |
| author_sort | Van Calster, B |
| collection | OXFORD |
| description | There is increasing awareness that the methodology and findings of research should be transparent. This includes studies using artificial intelligence to develop predictive algorithms that make individualized diagnostic or prognostic risk predictions. We argue that it is paramount to make the algorithm behind any prediction publicly available. This allows independent external validation, assessment of performance heterogeneity across settings and over time, and algorithm refinement or updating. Online calculators and apps may aid uptake if accompanied with sufficient information. For algorithms based on "black box" machine learning methods, software for algorithm implementation is a must. Hiding algorithms for commercial exploitation is unethical, because there is no possibility to assess whether algorithms work as advertised or to monitor when and how algorithms are updated. Journals and funders should demand maximal transparency for publications on predictive algorithms, and clinical guidelines should only recommend publicly available algorithms. |
| first_indexed | 2024-03-07T04:31:02Z |
| format | Journal article |
| id | oxford-uuid:ce53eca0-76d7-4e61-8e49-ddede88c59a1 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:31:02Z |
| publishDate | 2019 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | oxford-uuid:ce53eca0-76d7-4e61-8e49-ddede88c59a12022-03-27T07:34:51ZPredictive analytics in health care: how can we know it works?Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ce53eca0-76d7-4e61-8e49-ddede88c59a1EnglishSymplectic Elements at OxfordOxford University Press2019Van Calster, BWynants, LTimmerman, DSteyerberg, ECollins, GThere is increasing awareness that the methodology and findings of research should be transparent. This includes studies using artificial intelligence to develop predictive algorithms that make individualized diagnostic or prognostic risk predictions. We argue that it is paramount to make the algorithm behind any prediction publicly available. This allows independent external validation, assessment of performance heterogeneity across settings and over time, and algorithm refinement or updating. Online calculators and apps may aid uptake if accompanied with sufficient information. For algorithms based on "black box" machine learning methods, software for algorithm implementation is a must. Hiding algorithms for commercial exploitation is unethical, because there is no possibility to assess whether algorithms work as advertised or to monitor when and how algorithms are updated. Journals and funders should demand maximal transparency for publications on predictive algorithms, and clinical guidelines should only recommend publicly available algorithms. |
| spellingShingle | Van Calster, B Wynants, L Timmerman, D Steyerberg, E Collins, G Predictive analytics in health care: how can we know it works? |
| title | Predictive analytics in health care: how can we know it works? |
| title_full | Predictive analytics in health care: how can we know it works? |
| title_fullStr | Predictive analytics in health care: how can we know it works? |
| title_full_unstemmed | Predictive analytics in health care: how can we know it works? |
| title_short | Predictive analytics in health care: how can we know it works? |
| title_sort | predictive analytics in health care how can we know it works |
| work_keys_str_mv | AT vancalsterb predictiveanalyticsinhealthcarehowcanweknowitworks AT wynantsl predictiveanalyticsinhealthcarehowcanweknowitworks AT timmermand predictiveanalyticsinhealthcarehowcanweknowitworks AT steyerberge predictiveanalyticsinhealthcarehowcanweknowitworks AT collinsg predictiveanalyticsinhealthcarehowcanweknowitworks |