Voice over the Internet Protocol (VoIP) systems such as Adobe ConnectNow, Skype, ooVoo, etc. may include the use of software applications for telerehabilitation (TR) therapy that can provide voice and video teleconferencing between patients and therapists. Privacy and security applications as well as HIPAA compliance within these protocols have been questioned by information technologists, providers of care and other health care entities. This paper develops a privacy and security checklist that can be used within a VoIP system to determine if it meets privacy and security procedures and whether it is HIPAA compliant. Based on this analysis, specific HIPAA criteria that therapists and health care facilities should follow are outlined and discussed, and therapists must weigh the risks and benefits when deciding to use VoIP software for TR.
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http://dx.doi.org/10.5195/ijt.2010.6056 | DOI Listing |
Int J Eat Disord
January 2025
SEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Objective: Artificial intelligence (AI) could revolutionize the delivery of mental health care, helping to streamline clinician workflows and assist with diagnostic and treatment decisions. Yet, before AI can be integrated into practice, it is necessary to understand perspectives of these tools to inform facilitators and barriers to their uptake. We gathered data on clinician and community participant perspectives of incorporating AI in the clinical management of eating disorders.
View Article and Find Full Text PDFNeural Netw
January 2025
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China. Electronic address:
Due to the distinctive distributed privacy-preserving architecture, split learning has found widespread application in scenarios where computational resources on the client side are limited. Unlike clients in federated learning retaining the whole model, split learning partitions the model into two segments situated separately on the server and client ends, thereby preventing direct access to the complete model structure by either party and fortifying its resilience against attacks. However, existing studies have demonstrated that even with access restricted to partial model outputs, split learning remains susceptible to data reconstruction attacks.
View Article and Find Full Text PDFBMC 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.
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