Development and validation of a patient-level model to predict dementia across a network of observational databases

Autor: Luis H. John, Egill A. Fridgeirsson, Jan A. Kors, Jenna M. Reps, Ross D. Williams, Patrick B. Ryan, Peter R. Rijnbeek

Publikováno v: BMC Medicine, Vol 22, Iss 1, Pp 1-12 (2024)

Abstract Background A prediction model can be a useful tool to quantify the risk of a patient developing dementia in the next years and take risk-factor-targeted intervention. Numerous dementia prediction models have been developed, but few have been

Externí odkaz: https://doaj.org/article/fc208c44b82f4bab9139744e5d70852e

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network

Autor: Ross D. Williams, Aniek F. Markus, Cynthia Yang, Talita Duarte-Salles, Scott L. DuVall, Thomas Falconer, Jitendra Jonnagaddala, Chungsoo Kim, Yeunsook Rho, Andrew E. Williams, Amanda Alberga Machado, Min Ho An, María Aragón, Carlos Areia, Edward Burn, Young Hwa Choi, Iannis Drakos, Maria Tereza Fernandes Abrahão, Sergio Fernández-Bertolín, George Hripcsak, Benjamin Skov Kaas-Hansen, Prasanna L. Kandukuri, Jan A. Kors, Kristin Kostka, Siaw-Teng Liaw, Kristine E. Lynch, Gerardo Machnicki, Michael E. Matheny, Daniel Morales, Fredrik Nyberg, Rae Woong Park, Albert Prats-Uribe, Nicole Pratt, Gowtham Rao, Christian G. Reich, Marcela Rivera, Tom Seinen, Azza Shoaibi, Matthew E. Spotnitz, Ewout W. Steyerberg, Marc A. Suchard, Seng Chan You, Lin Zhang, Lili Zhou, Patrick B. Ryan, Daniel Prieto-Alhambra, Jenna M. Reps, Peter R. Rijnbeek

Publikováno v: BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-13 (2022)

Abstract Background We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Esti

Externí odkaz: https://doaj.org/article/da152b2f9d8848c687fd69d67eb875e5

Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability?

Autor: Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna M. Reps, Peter R. Rijnbeek, Jenna Wong, Ross D. Williams

Publikováno v: Caring is Sharing – Exploiting the Value in Data for Health and Innovation ISBN: 9781643683881

We investigated a stacking ensemble method that combines multiple base learners within a database. The results on external validation across four large databases suggest a stacking ensemble could improve model transportability.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7fecac1f6431ba713860e8d72bfd61b0
https://doi.org/10.3233/shti230080

Use of unstructured text in prognostic clinical prediction models: a systematic review

Autor: Tom M. Seinen, Egill Fridgeirsson, Solomon Ioannou, Daniel Jeannetot, Luis H. John, Jan A. Kors, Aniek F. Markus, Victor Pera, Alexandros Rekkas, Ross D. Williams, Cynthia Yang, Erik van Mulligen, Peter R. Rijnbeek

Publikováno v: Journal of the American Medical Informatics Association, 29(7), 1292-1302. Oxford University Press

Objective This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether usin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5049d802d53face1eeddf8738f2c4799
https://doi.org/10.1093/jamia/ocac058

Renin-angiotensin system blockers and susceptibility to COVID-19

Autor: Thomas Falconer, K van Bochove, Andrew E. Williams, Ross D. Williams, Michael E. Matheny, Carlos Areia, Harlan M. Krumholz, Morales, Albert Prats-Uribe, M Aragon, James Weaver, Martijn J. Schuemie, Lin Zhang, George Hripcsak, Scott L. DuVall, Daniel Prieto-Alhambra, Kristine E. Lynch, Nicole L. Pratt, Kristin Kostka, Rae Woong Park, Christophe G. Lambert, Cynthia Sung, T Duarte-Salles, Thamir M. Alshammari, Jce Lane, Fredrik Nyberg, Sergio Fernandez-Bertolin, Peter R. Rijnbeek, Patrick B. Ryan, Anthony G. Sena, Seng Chan You, Mitchell M. Conover, Marc A. Suchard

Publikováno v: medRxiv
The Lancet. Digital Health
article-version (status) pre
article-version (number) 1
The Lancet Digital Health
The Lancet Digital Health, 3(2), e98-e114. Elsevier Ltd.

Background Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and internation

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81dc8da03efe58fef3273faf80a9983f
https://doi.org/10.1016/S2589-7500(20)30289-2