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Digital Home-Based Self-Monitoring System for People with Heart Failure: Protocol for Development of SmartHeart and Evaluation of Feasibility and Acceptability.
JMIR Res Protoc
January 2025
School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Burwood, Australia.
Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.
View Article and Find Full Text PDFAdvancing stroke rehabilitation: the role of wearable technology according to research experts.
Disabil Rehabil Assist Technol
January 2025
School of Rehabilitation, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada.
Background: Advancements in wearable technology have created new opportunities to monitor stroke survivors' behaviors in daily activities. Research insights are needed to guide its adoption in clinical practice, address current gaps, and shape the future of stroke rehabilitation. This project aims to: (1) Understand stroke rehabilitation researchers' perspectives on the opportunities, challenges, and clinical relevance of wearable technology for stroke rehabilitation, and (2) Identify necessary next steps to integrate wearable technology in research and clinical practice.
View Article and Find Full Text PDFSimulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning.
Nucleic Acids Res
January 2025
Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, 0372, Norway.
Machine learning (ML) has shown great potential in the adaptive immune receptor repertoire (AIRR) field. However, there is a lack of large-scale ground-truth experimental AIRR data suitable for AIRR-ML-based disease diagnostics and therapeutics discovery. Simulated ground-truth AIRR data are required to complement the development and benchmarking of robust and interpretable AIRR-ML methods where experimental data is currently inaccessible or insufficient.
View Article and Find Full Text PDFCurrent state and promise of user-centered design to harness explainable AI in clinical decision-support systems for patients with CNS tumors.
Front Radiol
January 2025
Department of Biostatistics & Informatics, Colorado School of Public Health, Aurora, CO, United States.
In neuro-oncology, MR imaging is crucial for obtaining detailed brain images to identify neoplasms, plan treatment, guide surgical intervention, and monitor the tumor's response. Recent AI advances in neuroimaging have promising applications in neuro-oncology, including guiding clinical decisions and improving patient management. However, the lack of clarity on how AI arrives at predictions has hindered its clinical translation.
View Article and Find Full Text PDFIntroduction/purpose: Teleultrasound connects expert point-of-care ultrasound (POCUS) users with remote community and rural sites. Evolving technologies including handheld devices, upgraded image quality, and the ability to transmit over low bandwidth connections increase POCUS education, accessibility, and clinical integration. Potential teleultrasound venues include low-resource settings, prehospital care, and austere environments (high altitudes, microgravity, conflict zones, etc.
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