Hypermedia data browsing is a mean for improving information access. However, the overload and the heterogeneity of medical information, as well as the multitude of possible navigational paths, turn the consultation of data into a difficult task. We present in this paper a solution for the development of adaptive user interfaces in a hypermedia data browsing environment. It is based on the capitalization of the users knowledge in the decision-making process, expressed in terms of navigational paths and of data presentation modes that are customized to the user's preferences. This capitalization offers the user a way to reuse the cumulative experiences in browsing through patient records. We illustrate our approach with the implementation of HEMA, a clinical workstation prototype.
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BMC Health Serv Res
January 2025
Institute Patient-Centered Digital Health, Bern University of Applied Sciences, Quellgasse 21, Biel, 2502, Switzerland.
Background: Hospital at home (HaH) care models have gained significant attention due to their potential to reduce healthcare costs, improve patient satisfaction, and lower readmission rates. However, the lack of a standardized classification system has hindered systematic evaluation and comparison of these models. Taxonomies serve as classification systems that simplify complexity and enhance understanding within a specific domain.
View Article and Find Full Text PDFPLoS One
January 2025
School of Electronic Information Engineering, Inner Mongolia University, Hohhot, Inner Mongolia, China.
Cognitive Radio (CR) technology enables wireless devices to learn about their surrounding spectrum environment through sensing capabilities, thereby facilitating efficient spectrum utilization without interfering with the normal operation of licensed users. This study aims to enhance spectrum sensing in multi-user cooperative cognitive radio systems by leveraging a hybrid model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. A novel multi-user cooperative spectrum sensing model is developed, utilizing CNN's local feature extraction capability and LSTM's advantage in handling sequential data to optimize sensing accuracy and efficiency.
View Article and Find Full Text PDFJ Neurol
January 2025
Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Spitalstrasse 2, CH-4031, Basel, Switzerland.
Aim: As part of the development of a smartphone-based app for monitoring MS disease activity and progression (dreaMS, NCT05009160), we developed six gamified tests with multiple difficulty levels as a monitoring tool for cognition. This study quantified the relative difficulty between levels and investigated their reliability, ability to depict practice effects, and user acceptance.
Methods: Healthy volunteers played each game, covering five cognitive domains, twice per day for 11 consecutive days.
Wearable Technol
December 2024
Institute of Advanced Materials for Sustainable Manufacturing, Tecnologico de Monterrey, Monterrey 64849, Nuevo Leon, Mexico.
This paper explores the integration of haptic gloves and virtual reality (VR) environments to enhance industrial training and operational efficiency within the framework of Industry 4.0 and Industry 5.0.
View Article and Find Full Text PDFJMIR Rehabil Assist Technol
January 2025
Department of Health and Nursing Science, Faculty of Health and Sport Sciences, University of Agder, Kristiansand, Norway.
Background: Health care is shifting toward 5 proactive approaches: personalized, participatory, preventive, predictive, and precision-focused services (P5 medicine). This patient-centered care leverages technologies such as artificial intelligence (AI)-powered robots, which can personalize and enhance services for users with disabilities. These advancements are crucial given the World Health Organization's projection of a global shortage of up to 10 million health care workers by 2030.
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