The BBDTC (https://biobigdata.ucsd.edu) is a community-oriented platform to encourage high-quality knowledge dissemination with the aim of growing a well-informed biomedical big data community through collaborative efforts on training and education. The BBDTC is an e-learning platform that empowers the biomedical community to develop, launch and share open training materials. It deploys hands-on software training toolboxes through virtualization technologies such as Amazon EC2 and Virtualbox. The BBDTC facilitates migration of courses across other course management platforms. The framework encourages knowledge sharing and content personalization through the playlist functionality that enables unique learning experiences and accelerates information dissemination to a wider community.
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http://dx.doi.org/10.1016/j.jocs.2017.03.010 | DOI Listing |
NPJ Syst Biol Appl
January 2025
Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China.
Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results from variable responses across cancers, offering valuable prognostic insights.
View Article and Find Full Text PDFJ Biomech
January 2025
Department of Gastroenterology and Hepatology and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China; Med-X Center for Informatics, Sichuan University, Chengdu, Sichuan 610041, PR China. Electronic address:
Portal hypertension (PH) is the initial and main consequence of liver cirrhosis. Hepatic venous pressure gradient (HVPG) measurement has been widely used to estimate portal pressure gradient (PPG) and detect portal hypertension. However, some clinical studies have found poor correlation between HVPG and PPG, which may lead to the misdiagnosis of portal hypertension.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Anesthesiology and Critical Care, CHU Rouen, Rouen, France.
Background: Intensive care units (ICUs) handle the most critical patients with a high risk of mortality. Due to those conditions, close monitoring is necessary and therefore, a large volume of data is collected. Collaborative ventures have enabled the emergence of large open access databases, leading to numerous publications in the field.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Chronic Disease Epidemiology, Population and Public Health, Pennington Biomedical Research Center, Baton Rouge, LA, United States.
Background: Electronic health records (EHRs) facilitate the accessibility and sharing of patient data among various health care providers, contributing to more coordinated and efficient care.
Objective: This study aimed to summarize the evolution of secondary use of EHRs and their interoperability in medical research over the past 25 years.
Methods: We conducted an extensive literature search in the PubMed, Scopus, and Web of Science databases using the keywords Electronic health record and Electronic medical record in the title or abstract and Medical research in all fields from 2000 to 2024.
BMC Public Health
January 2025
Department of Maternal, Child & Adolescent Health, School of Public Health, Anhui Medical University, 81th Meishan Road, Hefei, 230032, Anhui Province, China.
Introduction: School-based universal depression screening (SBUDS) is an effective method for early identification of depression. As parents are the primary decision-makers for their children's acceptance of healthcare services, this study aims to examine rural and urban parental acceptance of SBUDS.
Methods: The study assessed parental acceptance of SBUDS for their children and its association with self-reported parental perception of depression (i.
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