Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jonathan I. Kennedy"'
Autor:
Anuradhaa Subramanian, Amaya Azcoaga-Lorenzo, Astha Anand, Katherine Phillips, Siang Ing Lee, Neil Cockburn, Adeniyi Francis Fagbamigbe, Christine Damase-Michel, Christopher Yau, Colin McCowan, Dermot O’Reilly, Gillian Santorelli, Holly Hope, Jonathan I. Kennedy, Kathryn M. Abel, Kelly-Ann Eastwood, Louise Locock, Mairead Black, Maria Loane, Ngawai Moss, Rachel Plachcinski, Shakila Thangaratinam, Sinead Brophy, Utkarsh Agrawal, Zoe Vowles, Peter Brocklehurst, Helen Dolk, Catherine Nelson-Piercy, Krishnarajah Nirantharakumar, on behalf of the MuM-PreDiCT Group
Publikováno v:
BMC Medicine, Vol 21, Iss 1, Pp 1-13 (2023)
Abstract Background The number of medications prescribed during pregnancy has increased over the past few decades. Few studies have described the prevalence of multiple medication use among pregnant women. This study aims to describe the overall prev
Externí odkaz:
https://doaj.org/article/3de01466eba041e88d0ea3b14fb0f209
Autor:
Siang Ing Lee, Amaya Azcoaga-Lorenzo, Utkarsh Agrawal, Jonathan I. Kennedy, Adeniyi Francis Fagbamigbe, Holly Hope, Anuradhaa Subramanian, Astha Anand, Beck Taylor, Catherine Nelson-Piercy, Christine Damase-Michel, Christopher Yau, Francesca Crowe, Gillian Santorelli, Kelly-Ann Eastwood, Zoe Vowles, Maria Loane, Ngawai Moss, Peter Brocklehurst, Rachel Plachcinski, Shakila Thangaratinam, Mairead Black, Dermot O’Reilly, Kathryn M. Abel, Sinead Brophy, Krishnarajah Nirantharakumar, Colin McCowan, on behalf of the MuM-PreDiCT Group
Publikováno v:
BMC Pregnancy and Childbirth, Vol 22, Iss 1, Pp 1-15 (2022)
Abstract Background Although maternal death is rare in the United Kingdom, 90% of these women had multiple health/social problems. This study aims to estimate the prevalence of pre-existing multimorbidity (two or more long-term physical or mental hea
Externí odkaz:
https://doaj.org/article/25f231e5d3254eb2a3d71bca5da07e43
Autor:
Fabiola Fernández-Gutiérrez, Jonathan I. Kennedy, Roxanne Cooksey, Mark Atkinson, Ernest Choy, Sinead Brophy, Lin Huo, Shang-Ming Zhou
Publikováno v:
Diagnostics, Vol 11, Iss 10, p 1908 (2021)
(1) Background: We aimed to develop a transparent machine-learning (ML) framework to automatically identify patients with a condition from electronic health records (EHRs) via a parsimonious set of features. (2) Methods: We linked multiple sources of
Externí odkaz:
https://doaj.org/article/416b45ceb3cc456caea9c675d0f831f7
Autor:
Siang Ing Lee, Holly Hope, Dermot O’Reilly, Lisa Kent, Gillian Santorelli, Anuradhaa Subramanian, Ngawai Moss, Amaya Azcoaga-Lorenzo, Adeniyi Francis Fagbamigbe, Catherine Nelson-Piercy, Christopher Yau, Colin McCowan, Jonathan I Kennedy, Katherine Phillips, Megha Singh, Mohamed Mhereeg, Neil Cockburn, Peter Brocklehurst, Rachel Plachcinski, Richard Riley, Shakila Thangaratinam, Sinead Brophy, Sudasing Pathirannehelage Buddhika Sudasinghe, Utkarsh Agrawal, Zoe Vowles, Kathryn M Abel, Krishnarajah Nirantharakumar, Mairead Black, Kelly-Ann Eastwood
IntroductionOne in five pregnant women have multiple long-term conditions in the United Kingdom (UK). Studies have shown that maternal multiple long-term conditions are associated with adverse outcomes. This observational study aims to compare matern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::535c59b5f14ccbebb585e3e66eaa105c
https://doi.org/10.1101/2022.08.26.22279213
https://doi.org/10.1101/2022.08.26.22279213
