Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Steven W J Nijman"'
Autor:
Gary S Collins, Richard D Riley, Johanna A A G Damen, Lotty Hooft, Ram Bajpai, Jie Ma, Constanza L Andaur Navarro, Toshihiko Takada, Steven W J Nijman, Paula Dhiman, Karel GM Moons
Publikováno v:
BMJ Open, Vol 10, Iss 11 (2020)
Introduction Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domains. Systematic reviews have shown that the methodological and reporting quality of prediction model st
Externí odkaz:
https://doaj.org/article/3a9beb531820437fbb035f610229206c
Autor:
T. Katrien J. Groenhof, Michiel L. Bots, Thomas P. A. Debray, Steven W J Nijman, Menno Brandjes, Karel G.M. Moons, Jeroen Hoogland, John J.L. Jacobs, Folkert W. Asselbergs
Publikováno v:
Journal of Clinical Epidemiology, 134, 22-34. Elsevier USA
Objectives: In clinical practice, many prediction models cannot be used when predictor values are missing. We, therefore, propose and evaluate methods for real-time imputation. Study Design and Setting: We describe (i) mean imputation (where missing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e095068e0d70fe812230cc93547db1d9
https://doi.org/10.1016/j.jclinepi.2021.01.003
https://doi.org/10.1016/j.jclinepi.2021.01.003
Autor:
Anne A. H. de Hond, Artuur M. Leeuwenberg, Lotty Hooft, Ilse M. J. Kant, Steven W. J. Nijman, Hendrikus J. A. van Os, Jiska J. Aardoom, Thomas P. A. Debray, Ewoud Schuit, Maarten van Smeden, Johannes B. Reitsma, Ewout W. Steyerberg, Niels H. Chavannes, Karel G. M. Moons
Publikováno v:
NPJ Digital Medicine
npj Digital Medicine, Vol 5, Iss 1, Pp 1-13 (2022)
npj Digital Medicine, 5(1). NATURE PORTFOLIO
npj Digital Medicine, Vol 5, Iss 1, Pp 1-13 (2022)
npj Digital Medicine, 5(1). NATURE PORTFOLIO
While the opportunities of ML and AI in healthcare are promising, the growth of complex data-driven prediction models requires careful quality and applicability assessment before they are applied and disseminated in daily practice. This scoping revie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91ffe7e04b44968dde77247934b27baf
http://europepmc.org/articles/PMC8748878
http://europepmc.org/articles/PMC8748878
Autor:
Lotty Hooft, Steven W J Nijman, Jie Ma, Johanna A A G Damen, Gary S. Collins, Paula Dhiman, Karel G.M. Moons, Constanza L Andaur Navarro, Ram Bajpai, Richard D Riley, Toshihiko Takada
Publikováno v:
The BMJ
BMJ
BMJ
Objective To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties. Design Systematic review. Data sources PubMed from 1 January 2018 to 31 December 2019. Eligibil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a71b5de96d3d5d73e2298cb1290e9491
https://pubmed.ncbi.nlm.nih.gov/34670780
https://pubmed.ncbi.nlm.nih.gov/34670780
Autor:
Toshihiko Takada, Alicia Uijl, Steven W J Nijman, Thomas P. A. Debray, Kym I E Snell, Folkert W. Asselbergs, Spiros Denaxas, Tri-Long Nguyen
Publikováno v:
Takada, T, Nijman, S, Denaxas, S, Snell, K I E, Uijl, A, Nguyen, T-L, Asselbergs, F W & Debray, T P A 2021, ' Internal-external cross-validation helped to evaluate the generalizability of prediction models in large clustered datasets ', Journal of Clinical Epidemiology, vol. 137, pp. 83-91 . https://doi.org/10.1016/j.jclinepi.2021.03.025
Journal of clinical epidemiology, 137, 83-91. Elsevier USA
Journal of clinical epidemiology, 137, 83-91. Elsevier USA
Objective To illustrate how to evaluate the need of complex strategies for developing generalizable prediction models in large clustered datasets. Study Design and Setting We developed eight Cox regression models to estimate the risk of heart failure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b7dcf17f8146b6acbf78f75e8c7e985
Autor:
Thomas P. A. Debray, Jeroen Hoogland, John J.L. Jacobs, Michiel L. Bots, Ucc-Smart study groups, Karel G.M. Moons, Menno Brandjes, T. Katrien J. Groenhof, Steven W J Nijman, Folkert W. Asselbergs
Publikováno v:
European Heart Journal-Digital Health, 2(1), 154-164
Nijman, S W J, Hoogland, J, Groenhof, T K J, Brandjes, M, Jacobs, J J L, Bots, M L, Asselbergs, F W, Moons, K G M & Debray, T P A 2021, ' Real-time imputation of missing predictor values in clinical practice ', European Heart Journal-Digital Health, vol. 2, no. 1, pp. 154-164 . https://doi.org/10.1093/ehjdh/ztaa016
Nijman, S W J, Hoogland, J, Groenhof, T K J, Brandjes, M, Jacobs, J J L, Bots, M L, Asselbergs, F W, Moons, K G M & Debray, T P A 2021, ' Real-time imputation of missing predictor values in clinical practice ', European Heart Journal-Digital Health, vol. 2, no. 1, pp. 154-164 . https://doi.org/10.1093/ehjdh/ztaa016
Use of prediction models is widely recommended by clinical guidelines, but usually requires complete information on all predictors that is not always available in daily practice. We describe two methods for real-time handling of missing predictor val
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58eefa6bea758e7e7f3a15ec65a226ec
http://arxiv.org/abs/2012.01099
http://arxiv.org/abs/2012.01099
Autor:
Constanza L. Andaur Navarro, Johanna A. A. Damen, Toshihiko Takada, Steven W. J. Nijman, Paula Dhiman, Jie Ma, Gary S. Collins, Ram Bajpai, Richard D. Riley, Karel G. M. Moons, Lotty Hooft
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-13 (2022)
Abstract Background While many studies have consistently found incomplete reporting of regression-based prediction model studies, evidence is lacking for machine learning-based prediction model studies. We aim to systematically review the adherence o
Externí odkaz:
https://doaj.org/article/ded1a80e1b54492db40c644dfe0bc26a