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Increasing Access to Mental Health Supports for 18- to 25-Year-Old Indigenous Youth With the JoyPop Mobile Mental Health App: Study Protocol for a Randomized Controlled Trial.
JMIR Res Protoc
January 2025
Department of Psychology, Lakehead University, Thunder Bay, ON, Canada.
Background: Transitional-aged youth have a high burden of mental health difficulties in Canada, with Indigenous youth, in particular, experiencing additional circumstances that challenge their well-being. Mobile health (mHealth) approaches hold promise for supporting individuals in areas with less access to services such as Northern Ontario.
Objective: The primary objective of this study is to evaluate the effectiveness of the JoyPop app in increasing emotion regulation skills for Indigenous transitional-aged youth (aged 18-25 years) on a waitlist for mental health services when compared with usual practice (UP).
Designing Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.
J Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFCurrent and Future Role of Circulating DNA in the Diagnosis and Management of Urothelial Carcinoma.
Am Soc Clin Oncol Educ Book
January 2025
Division of Oncology, Department of Medicine, University of Washington, Seattle, WA.
The growing sophistication of tumor molecular profiling has helped to slowly transition oncologic care toward a more personalized approach in different tumor types, including in bladder cancer. The National Comprehensive Cancer Network recommends that all patients with stage IVA and stage IVB urothelial carcinoma have molecular analysis that integrates at least testing to help facilitate the selection of future therapeutic options. Sequencing of tumor-derived tissue is the mainstay to obtain this genomic testing, but as in other cancers, there has been extensive research into the integration of liquid biopsies in longitudinal management.
View Article and Find Full Text PDFClinical Evaluation of the NaviNetics Stereotactic System Using Intraoperative Portable Surgical Imaging System in DBS Surgery.
Oper Neurosurg (Hagerstown)
November 2024
Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Background And Objectives: A typical workflow for deep brain stimulation (DBS) surgery consists of head frame placement, followed by stereotactic computed tomography (CT) or MRI before surgical implantation of the hardware. At some institutions, this workflow is prolonged when the imaging scanner is located far away from the operating room, thereby increasing workflow times by the addition of transport times. Recently, the intraoperative O-arm has been shown to provide accurate image fusion with preoperative CT or MR imaging, suggesting the possibility of obtaining an intraoperative localization scan and postoperative confirmation.
View Article and Find Full Text PDFISLRWR: A network diffusion algorithm for drug-target interactions prediction.
PLoS One
January 2025
Shanghai Xinhao Information Technology Co., Ltd., Shanghai, China.
Machine learning techniques and computer-aided methods are now widely used in the pre-discovery tasks of drug discovery, effectively improving the efficiency of drug development and reducing the workload and cost. In this study, we used multi-source heterogeneous network information to build a network model, learn the network topology through multiple network diffusion algorithms, and obtain compressed low-dimensional feature vectors for predicting drug-target interactions (DTIs). We applied the metropolis-hasting random walk (MHRW) algorithm to improve the performance of the random walk with restart (RWR) algorithm, forming the basis by which the self-loop probability of the current node is removed.
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