J
Jenny Tran
Researcher at University of Oxford
Publications - 18
Citations - 1368
Jenny Tran is an academic researcher from University of Oxford. The author has contributed to research in topics: Population & Blood pressure. The author has an hindex of 11, co-authored 18 publications receiving 775 citations. Previous affiliations of Jenny Tran include University of New South Wales & University of Sydney.
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Journal ArticleDOI
Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals.
Nathalie Conrad,Andrew Judge,Andrew Judge,Andrew Judge,Jenny Tran,Hamid Mohseni,Deborah Hedgecott,Abel Perez Crespillo,Moira Allison,Harry Hemingway,Harry Hemingway,John G.F. Cleland,John G.F. Cleland,John J.V. McMurray,Kazem Rahimi,Kazem Rahimi +15 more
TL;DR: A moderate decline in standardised incidence of heart failure in the UK is increasing, and is now similar to the four most common causes of cancer combined, while Socioeconomically deprived individuals were more likely to develop heart failure than were affluent individuals.
Journal ArticleDOI
Deep learning for electronic health records: A comparative review of multiple deep neural architectures
Jose Roberto Ayala Solares,Jose Roberto Ayala Solares,Francesca Raimondi,Yajie Zhu,Fatemeh Rahimian,Dexter Canoy,Dexter Canoy,Dexter Canoy,Jenny Tran,Ana Catarina Pinho Gomes,Amir H. Payberah,Mariagrazia Zottoli,Milad Nazarzadeh,Nathalie Conrad,Kazem Rahimi,Kazem Rahimi,Gholamreza Salimi-Khorshidi +16 more
TL;DR: This paper aims to provide a comparative review of the key deep learning architectures that have been applied to EHR data, and introduces and uses one of the world's largest and most complex linked primary care EHR datasets as a new asset for training such data-hungry models.
Journal ArticleDOI
Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study.
Jenny Tran,Jenny Tran,Robyn Norton,Nathalie Conrad,Fatemeh Rahimian,Fatemeh Rahimian,Dexter Canoy,Dexter Canoy,Milad Nazarzadeh,Kazem Rahimi,Kazem Rahimi +10 more
TL;DR: The burden of multimorbidity and comorbidities in patients with incident non-fatal CVD increased between 2000 and 2014, and on average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbbidities, but the type of comor bidities varied by age and sex.
Journal ArticleDOI
Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records
Fatemeh Rahimian,Fatemeh Rahimian,Gholamreza Salimi-Khorshidi,Gholamreza Salimi-Khorshidi,Amir H. Payberah,Amir H. Payberah,Jenny Tran,Jenny Tran,Roberto Ayala Solares,Roberto Ayala Solares,Francesca Raimondi,Francesca Raimondi,Milad Nazarzadeh,Milad Nazarzadeh,Dexter Canoy,Dexter Canoy,Kazem Rahimi,Kazem Rahimi +17 more
TL;DR: The use of machine learning and addition of temporal information led to substantially improved discrimination and calibration for predicting the risk of emergency admission and support the potential of incorporating machine learning models into electronic health records to inform care and service planning.
Journal ArticleDOI
Dysferlin, annexin A1, and mitsugumin 53 are upregulated in muscular dystrophy and localize to longitudinal tubules of the T-system with stretch.
Leigh B. Waddell,Frances A. Lemckert,Xi F. Zheng,Jenny Tran,Frances J. Evesson,J. Hawkes,Angela Lek,Neil E. Street,Pei-Hui Lin,Nigel F. Clarke,Andrew P. Landstrom,Michael J. Ackerman,Noah Weisleder,Jianjie Ma,Kathryn N. North,Sandra T. Cooper +15 more
TL;DR: Results suggest that longitudinal tubules of the t-system may represent sites of physiological membrane damage targeted by this membrane repair complex, and suggest that MG53 is unlikely to be a common cause of muscular dystrophy in Australia.