Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Jenna M. Reps"'
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
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-17 (2024)
Abstract Background There is currently no consensus on the impact of class imbalance methods on the performance of clinical prediction models. We aimed to empirically investigate the impact of random oversampling and random undersampling, two commonl
Externí odkaz:
https://doaj.org/article/16e1370b11874d648d085a5e82d580c9
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-12 (2022)
Abstract Background Many dementia prediction models have been developed, but only few have been externally validated, which hinders clinical uptake and may pose a risk if models are applied to actual patients regardless. Externally validating an exis
Externí odkaz:
https://doaj.org/article/210c55b2c05446eb893d728559eab880
Publikováno v:
BMC Pregnancy and Childbirth, Vol 22, Iss 1, Pp 1-11 (2022)
Abstract Background Perinatal depression is estimated to affect ~ 12% of pregnancies and is linked to numerous negative outcomes. There is currently no model to predict perinatal depression at multiple time-points during and after pregnancy using var
Externí odkaz:
https://doaj.org/article/7a131dbda945485f88368f210f38d8f2
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
Autor:
Anastasiya Nestsiarovich, Jenna M. Reps, Michael E. Matheny, Scott L. DuVall, Kristine E. Lynch, Maura Beaton, Xinzhuo Jiang, Matthew Spotnitz, Stephen R. Pfohl, Nigam H. Shah, Carmen Olga Torre, Christian G. Reich, Dong Yun Lee, Sang Joon Son, Seng Chan You, Rae Woong Park, Patrick B. Ryan, Christophe G. Lambert
Publikováno v:
Translational Psychiatry, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidit
Externí odkaz:
https://doaj.org/article/c4de8fea768b435d9121377e5657d19c
Publikováno v:
Frontiers in Drug Safety and Regulation, Vol 2 (2022)
When developing predictive models, model simplicity and performance often need to be balanced. We propose a novel methodology to put the performance of bleeding risk prediction models ORBIT, ATRIA, HAS-BLED, CHADS2, and CHA2DS2-VASc into perspective.
Externí odkaz:
https://doaj.org/article/f0640eb9f78b4c0689a9fa010865779d
Publikováno v:
Journal of Big Data, Vol 8, Iss 1, Pp 1-18 (2021)
Abstract Background The design used to create labelled data for training prediction models from observational healthcare databases (e.g., case-control and cohort) may impact the clinical usefulness. We aim to investigate hypothetical design issues an
Externí odkaz:
https://doaj.org/article/f6ab786bb9aa4bab840b17808716db32
Autor:
Jill Hardin, Jenna M. Reps
Publikováno v:
BMC Medical Research Methodology, Vol 21, Iss 1, Pp 1-9 (2021)
Abstract Background The goal of our study is to examine the impact of the lookback length when engineering features to use in developing predictive models using observational healthcare data. Using a longer lookback for feature engineering gives more
Externí odkaz:
https://doaj.org/article/3b69d818175b4137b5af1110bf2e9c0f
Autor:
Jenna M. Reps, Peter Rijnbeek, Alana Cuthbert, Patrick B. Ryan, Nicole Pratt, Martijn Schuemie
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-24 (2021)
Abstract Background Researchers developing prediction models are faced with numerous design choices that may impact model performance. One key decision is how to include patients who are lost to follow-up. In this paper we perform a large-scale empir
Externí odkaz:
https://doaj.org/article/9ea5a25701404fa0bb3b3373ca50d129