Being able to track, analyze, and use data from continuous glucose monitors (CGMs) and through platforms and apps that communicate with CGMs helps achieve better outcomes and can advance the understanding of diabetes. The risks to patients' expectation of privacy are great, and their ability to control how their information is collected, stored, and used is virtually nonexistent. Patients' physical security is also at risk if adequate cybersecurity measures are not taken. Currently, data privacy and security protections are not robust enough to address the privacy and security risks and stymies the current and future benefits of CGM and the platforms and apps that communicate with them.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5478039 | PMC |
http://dx.doi.org/10.1177/1932296816681585 | DOI Listing |
BMC Public Health
January 2025
Department of Public Health and Primary Care, Leiden University Medical Centre, Hippocratespad 21, Leiden, Netherlands.
Background: eHealth literacy (eHL) is positively associated with health-related behaviors and outcomes. Previous eHL studies primarily collected data from online users and seldom focused on the general population in low- and middle-income countries (LMIC). Additionally, knowledge about factors that affect eHL is limited.
View Article and Find Full Text PDFMethods
January 2025
School of Computer Science and Engineering, Central South University, Changsha 410083, China; Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China.
Compound-protein interaction (CPI) prediction is critical in the early stages of drug discovery, narrowing the search space for CPIs and reducing the cost and time required for traditional high-throughput screening. However, CPI-related data are usually distributed across different institutions and their sharing is restricted because of data privacy and intellectual property rights. Constructing a scheme that enhances multi-institutional collaboration to improve prediction accuracy while protecting data privacy is essential.
View Article and Find Full Text PDFIntroduction: Sharing patient health information and biospecimens can improve health outcomes and accelerate breakthroughs in medical research. But patients generally lack understanding of how their clinical data and biospecimens are used or commercialized for research. In this mixed methods project, we assessed the impact of communication materials on patient understanding, attitudes, and perceptions.
View Article and Find Full Text PDFJ Med Educ Curric Dev
January 2025
Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, NY, USA.
Objectives: Instilling the principles of ethical and responsible medical research is critical for educating the next generation of clinical researchers. We developed a responsible conduct of research (RCR) workshop and associated curriculum for undergraduate trainees in a quantitative clinical research program.
Methods: Topics in this 7-module RCR workshop are relevant to undergraduate trainees in quantitative fields, many of whom are learning about these concepts for the first time.
Cureus
December 2024
Medical Education, ABWA Medical College, Faisalabad, PAK.
Background: The inclusion of artificial intelligence in medical education, specifically through the use of ChatGPT (OpenAI, San Francisco, CA), has transformed learning and generated many ethical questions. This study aims to analyze the medical students' ethical concerns about using ChatGPT in medical education, focusing on privacy, accuracy, and professional integrity.
Methods: The study format was a cross-sectional survey distributed to 219 medical students at ABWA Medical College, Pakistan.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!