Jenna Reps
Jenna Reps
Researchers of Computer Science, Nottingham University
Verified email at - Homepage
Cited by
Cited by
Can machine-learning improve cardiovascular risk prediction using routine clinical data?
SF Weng, J Reps, J Kai, JM Garibaldi, N Qureshi
PloS one 12 (4), e0174944, 2017
Safety of hydroxychloroquine, alone and in combination with azithromycin, in light of rapid wide-spread use for COVID-19: a multinational, network cohort and self-controlled …
JCE Lane, J Weaver, K Kostka, T Duarte-Salles, MTF Abrahao, H Alghoul, ...
MedRXiv, 2020
Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data
JM Reps, MJ Schuemie, MA Suchard, PB Ryan, PR Rijnbeek
Journal of the American Medical Informatics Association 25 (8), 969-975, 2018
Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study
JCE Lane, J Weaver, K Kostka, T Duarte-Salles, MTF Abrahao, H Alghoul, ...
The Lancet Rheumatology 2 (11), e698-e711, 2020
Comparing stochastic differential equations and agent-based modelling and simulation for early-stage cancer
GP Figueredo, PO Siebers, MR Owen, J Reps, U Aickelin
PloS one 9 (4), e95150, 2014
Finding treatment‐resistant depression in real‐world data: How a data‐driven approach compares with expert‐based heuristics
MS Cepeda, J Reps, D Fife, C Blacketer, P Stang, P Ryan
Depression and anxiety 35 (3), 220-228, 2018
Comparison of algorithms that detect drug side effects using electronic healthcare databases
JM Reps, JM Garibaldi, U Aickelin, D Soria, J Gibson, R Hubbard
Soft Computing 17 (12), 2381-2397, 2013
Finding factors that predict treatment‐resistant depression: Results of a cohort study
MS Cepeda, J Reps, P Ryan
Depression and anxiety 35 (7), 668-673, 2018
Quiet in class: classification, noise and the dendritic cell algorithm
F Gu, J Feyereisl, R Oates, J Reps, J Greensmith, U Aickelin
International Conference on Artificial Immune Systems, 173-186, 2011
Illness beliefs predict mortality in patients with diabetic foot ulcers
K Vedhara, K Dawe, JNV Miles, MA Wetherell, N Cullum, C Dayan, ...
PloS one 11 (4), e0153315, 2016
Seek COVER: Development and validation of a personalized risk calculator for COVID-19 outcomes in an international network
RD Williams, AF Markus, C Yang, TD Salles, T Falconer, J Jonnagaddala, ...
MedRxiv, 2020
Using machine learning applied to real-world healthcare data for predictive analytics: an applied example in bariatric surgery
SS Johnston, JM Morton, I Kalsekar, EM Ammann, CW Hsiao, J Reps
Value in Health 22 (5), 580-586, 2019
A supervised adverse drug reaction signalling framework imitating Bradford Hill’s causality considerations
JM Reps, JM Garibaldi, U Aickelin, JE Gibson, RB Hubbard
Journal of biomedical informatics 56, 356-368, 2015
Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network
Q Wang, JM Reps, KF Kostka, PB Ryan, Y Zou, EA Voss, PR Rijnbeek, ...
PloS one 15 (1), e0226718, 2020
Discovering sequential patterns in a UK general practice database
J Reps, JM Garibaldi, U Aickelin, D Soria, JE Gibson, RB Hubbard
Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and …, 2012
Perinatal depressive symptoms often start in the prenatal rather than postpartum period: results from a longitudinal study
M Wilcox, BA McGee, DF Ionescu, M Leonte, L LaCross, J Reps, ...
Archives of women's mental health 24 (1), 119-131, 2021
Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining
JM Reps, U Aickelin, RB Hubbard
Computers in biology and medicine 69, 61-70, 2016
Refining adverse drug reactions using association rule mining for electronic healthcare data
JM Reps, U Aickelin, J Ma, Y Zhang
2014 IEEE International Conference on Data Mining Workshop, 763-770, 2014
Feasibility and evaluation of a large-scale external validation approach for patient-level prediction in an international data network: validation of models predicting stroke …
JM Reps, RD Williams, SC You, T Falconer, E Minty, A Callahan, PB Ryan, ...
BMC medical research methodology 20 (1), 1-10, 2020
Signalling paediatric side effects using an ensemble of simple study designs
JM Reps, JM Garibaldi, U Aickelin, D Soria, JE Gibson, RB Hubbard
Drug safety 37 (3), 163-170, 2014
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