Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Ruth M Reeves"'
Autor:
Alex H S Harris, Mark A Ilgen, Esther Lydia Meerwijk, Suzanne R Tamang, Andrea K Finlay, Ruth M Reeves
Publikováno v:
BMJ Open, Vol 12, Iss 8 (2022)
Introduction The state-of-the-art 3-step Theory of Suicide (3ST) describes why people consider suicide and who will act on their suicidal thoughts and attempt suicide. The central concepts of 3ST—psychological pain, hopelessness, connectedness, and
Externí odkaz:
https://doaj.org/article/3971bc040a00473a9703a72677fa64b9
Publikováno v:
Heliyon, Vol 10, Iss 5, Pp e26434- (2024)
Objective: Assigning outcome labels to large observational data sets in a timely and accurate manner, particularly when outcomes are rare or not directly ascertainable, remains a significant challenge within biomedical informatics. We examined whethe
Externí odkaz:
https://doaj.org/article/ff4847acb53f40bcb54ead2a6e99981c
Autor:
Jeremiah R. Brown, Iben M. Ricket, Ruth M. Reeves, Rashmee U. Shah, Christine A. Goodrich, Glen Gobbel, Meagan E. Stabler, Amy M. Perkins, Freneka Minter, Kevin C. Cox, Chad Dorn, Jason Denton, Bruce E. Bray, Ramkiran Gouripeddi, John Higgins, Wendy W. Chapman, Todd MacKenzie, Michael E. Matheny
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 11, Iss 7 (2022)
Background Social risk factors influence rehospitalization rates yet are challenging to incorporate into prediction models. Integration of social risk factors using natural language processing (NLP) and machine learning could improve risk prediction
Externí odkaz:
https://doaj.org/article/8eeaa93660b34a4eb7587d857b0b09d8
Autor:
Ivan Protsyuk, Martin G. Seneviratne, Andre Saraiva, Natalie Harris, Hugh Montgomery, Mustafa Suleyman, Xavier Glorot, Dominic King, Jack W. Rae, Clifton R. Baker, Alistair Connell, Suman V. Ravuri, Trevor Back, Clemens Meyer, Nenad Tomasev, Harry Askham, Michal Zielinski, Ruth M. Reeves, Joseph R. Ledsam, Shakir Mohamed, Thomas F. Osborne, Cian Hughes, Chris Laing, Alan Karthikesalingam, Valerio Magliulo, Anne Mottram, Christopher Nielson, Sebastien Baur, Julien Cornebise, Demis Hassabis, Geraint Rees
Publikováno v:
Nature Protocols. 16:2765-2787
Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electron
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1547705a8f9b73ddd1995e08dd7f633d
https://doi.org/10.1038/s41596-021-00513-5
https://doi.org/10.1038/s41596-021-00513-5
Autor:
Hugh Montgomery, Alan Karthikesalingam, Xavier Glorot, Christopher Nielson, Harry Askham, Suman V. Ravuri, Trevor Back, Joseph R. Ledsam, Michal Zielinski, Kelly S. Peterson, Geraint Rees, Alistair Connell, Nenad Tomasev, Julien Cornebise, Ivan Protsyuk, Andre Saraiva, Demis Hassabis, Cian Hughes, Chris Laing, Ruth M. Reeves, Shakir Mohamed, Dominic King, Anne Mottram, Jack W. Rae, Mustafa Suleyman, Clemens Meyer, Clifton R. Baker
Publikováno v:
Nature
The early prediction of deterioration could have an important role in supporting healthcare professionals, as an estimated 11% of deaths in hospital follow a failure to promptly recognize and treat deteriorating patients1. To achieve this goal requir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3716eea45fa33fb37c38efb1a54cdd0
https://doi.org/10.1038/s41586-019-1390-1
https://doi.org/10.1038/s41586-019-1390-1
Autor:
Amy M. Sitapati, Serguei V. S. Pakhomov, Hongfang Liu, Swapna Abhyankar, Jianfu Li, Theresa Cullen, Robert Murphy, Elizabeth Hanchrow, Hua Xu, Xiaoqian Jiang, Ruth M. Reeves, Jian-Guo Bian, Lucila Ohno-Machado, Michael E. Matheny, Scott L. DuVall, Karthik Natarajan, Kristine E. Lynch, Xiao Dong, Ekin Soysal, Jami Deckard
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association
Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b98b9d537df02a75cbf3322c0149ec63
http://europepmc.org/articles/PMC7337837
http://europepmc.org/articles/PMC7337837
Autor:
Rashmee U. Shah, Christine A. Goodrich, Andrew R. Bohm, Iben Ricket, Bruce E. Bray, Freneka F. Minter, Jeremiah R. Brown, Mike Conway, Lee M. Christensen, Michael E. Matheny, Wendy W. Chapman, Ruth M. Reeves, Maxwell Levis, Glenn T. Gobbel
Publikováno v:
J Biomed Inform
Social determinants of health (SDoH) are increasingly important factors for population health, healthcare outcomes, and care delivery. However, many of these factors are not reliably captured within structured electronic health record (EHR) data. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::476599fb596d5b6874f6a0152d4e7d6c
https://doi.org/10.1016/j.jbi.2021.103851
https://doi.org/10.1016/j.jbi.2021.103851
Autor:
Jason Denton, Aize Cao, Fern FitzHenry, Guanhua Chen, Svetlana K. Eden, Hui Cao, Michael E. Matheny, Ruth M. Reeves, Glenn T. Gobbel, Nancy Wells
Publikováno v:
Pain Research and Management, Vol 2020 (2020)
Pain Research & Management
Pain Research & Management
Objectives. This research describes the prevalence and covariates associated with opioid-induced constipation (OIC) in an observational cohort study utilizing a national veteran cohort and integrated data from the Center for Medicare and Medicaid Ser
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4728bf49e3ad2acc9d355f0d87057b9d
https://pubmed.ncbi.nlm.nih.gov/32318129
https://pubmed.ncbi.nlm.nih.gov/32318129
Autor:
Ivan Protsyuk, Xavier Glorot, Christopher Nielson, Alistair Connell, Cian Hughes, Shakir Mohamed, Chris Laing, Julien Cornebise, Andre Saraiva, Ruth M. Reeves, Demis Hassabis, Alan Karthikesalingam, Hugh Montgomery, Jack W. Rae, Clemens Meyer, Dominic King, Mustafa Suleyman, Suman V. Ravuri, Michal Zielinski, Anne Mottram, Harry Askham, Geraint Rees, Joseph R. Ledsam, Clifton R. Baker, Nenad Tomasev, Kelly S. Peterson, Trevor Back
Early detection of patient deterioration is key to unlocking the potential for targeted preventative care and improving patient outcomes. This protocol describes a workflow for developing deep learning continuous risk models for early prediction of f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca81db07e34dd4c756362e089da89768
https://doi.org/10.21203/rs.2.10083/v1
https://doi.org/10.21203/rs.2.10083/v1
Autor:
Jennifer H. Garvin, Paul A. Heidenreich, Mary K. Goldstein, Megha Kalsy, Michael E. Matheny, Bruce E. Bray, Ruth M. Reeves, Dan Bolton, Natalie Kelly, Glenn T. Gobbel, Stéphane M. Meystre, Julia Heavirland, Youngjun Kim, Andrew Redd
Publikováno v:
JMIR Medical Informatics
Background: We developed an accurate, stakeholder-informed, automated, natural language processing (NLP) system to measure the quality of heart failure (HF) inpatient care, and explored the potential for adoption of this system within an integrated h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fa479992caa9f757dac801aede98705
https://pubmed.ncbi.nlm.nih.gov/29335238
https://pubmed.ncbi.nlm.nih.gov/29335238