Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Terrence C. Lee"'
Autor:
Terrence C. Lee, BS, Bharanidharan Radha Saseendrakumar, MS, Mahasweta Nayak, Alison X. Chan, BS, John J. McDermott, IV, BA, Bita Shahrvini, BS, Gordon Y. Ye, Amy M. Sitapati, MD, Camille Nebeker, EdD, MS, Sally L. Baxter, MD, MSc
Publikováno v:
Ophthalmology Science, Vol 2, Iss 2, Pp 100151- (2022)
Purpose: To quantify and characterize social determinants of health (SDoH) data coverage using single-center electronic health records (EHRs) and the National Institutes of Health All of Us research program. Design: Retrospective cohort study from Ju
Externí odkaz:
https://doaj.org/article/94b2f854db264083ae523fbd3aa1ca38
Autor:
John J. McDermott, IV, BA, Terrence C. Lee, BS, Alison X. Chan, BS, Gordon Y. Ye, Bita Shahrvini, BS, Bharanidharan Radha Saseendrakumar, MS, Henry Ferreyra, MD, Eric Nudleman, MD, PhD, Sally L. Baxter, MD, MSc
Publikováno v:
Ophthalmology Science, Vol 2, Iss 1, Pp 100099- (2022)
Purpose: To assess for risk factors for retinal vein occlusion (RVO) among participants in the National Institutes of Health All of Us database, particularly social risk factors that have not been well studied, including substance use. Design: Retros
Externí odkaz:
https://doaj.org/article/75b782b3e6114efea873abaffe0615c2
Autor:
Alison X. Chan, John J. McDermott IV, Terrence C. Lee, Gordon Y. Ye, Bita Shahrvini, Bharanidharan Radha Saseendrakumar, Sally L. Baxter
Publikováno v:
PLoS ONE, Vol 17, Iss 6 (2022)
Purpose Inadequacies in healthcare access and utilization substantially impact outcomes for diabetic patients. The All of Us database offers extensive survey data pertaining to social determinants that is not routinely available in electronic health
Externí odkaz:
https://doaj.org/article/2ce1ba7df5154cfc9d43646182f9d5d8
Publikováno v:
Informatics, Vol 7, Iss 3, p 25 (2020)
Predictive analytics using electronic health record (EHR) data have rapidly advanced over the last decade. While model performance metrics have improved considerably, best practices for implementing predictive models into clinical settings for point-
Externí odkaz:
https://doaj.org/article/a968b883a0d247cf9225b20c5e527931
Autor:
Terrence C. Lee, Bharanidharan Radha Saseendrakumar, Mahasweta Nayak, Alison X. Chan, John J. McDermott, Bita Shahrvini, Gordon Y. Ye, Amy M. Sitapati, Camille Nebeker, Sally L. Baxter
Publikováno v:
Ophthalmology science, vol 2, iss 2
PurposeTo quantify and characterize social determinants of health (SDoH) data coverage using single-center electronic health records (EHRs) and the National Institutes of Health All of Us research program.DesignRetrospective cohort study from June 20
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80988489a0efcc1010818e0211d443da
https://escholarship.org/uc/item/3t16j8dr
https://escholarship.org/uc/item/3t16j8dr
Autor:
Edmund Men Qiao, Alexander Qian, David J Mariano, Terrence C. Lee, Eventine Youngblood, Linda Chou, James Don Murphy
Publikováno v:
Journal of Clinical Oncology. 40:6549-6549
6549 Background: The incidence of adolescent and young adults (AYAs) with cancer continues to increase. The psychosocial burden of early cancer diagnosis within this unique AYA population remains poorly characterized. Without proper resources, these
Publikováno v:
Informatics
Volume 7
Issue 3
Informatics (MDPI)
Informatics, Vol 7, Iss 25, p 25 (2020)
Volume 7
Issue 3
Informatics (MDPI)
Informatics, Vol 7, Iss 25, p 25 (2020)
Predictive analytics using electronic health record (EHR) data have rapidly advanced over the last decade. While model performance metrics have improved considerably, best practices for implementing predictive models into clinical settings for point-
Autor:
James D. Murphy, Edmund M. Qiao, Alexander S. Qian, Terrence C. Lee, Rohith S. Voora, Vinit Nalawade, Nikhil V. Kotha, Christian Dameff, Christopher J. Coyne
Publikováno v:
Journal of Clinical Oncology. 39:1512-1512
1512 Background: Elderly hospitalized cancer patients face high risks of inpatient hospital mortality. Identifying patients at high risk of hospital mortality could help with risk stratification, and potentially help inform future interventions aimed
Autor:
Christopher J. Coyne, Alexander S. Qian, Vinit Nalawade, Christian Dameff, Terrence C. Lee, Rohith S. Voora, Nikhil V. Kotha, James D. Murphy, Edmund M. Qiao
Publikováno v:
Journal of Clinical Oncology. 39:e22019-e22019
e22019 Background: Pediatric cancer patients represent a vulnerable cohort at risk of adverse outcomes after presenting to the emergency department (ED). Given the severity of cancer-related complications and uniqueness of this population, approaches