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Embracing the Digital Era for Greater Impact and Accessibility.
Health Educ Behav
December 2024
University of California San Francisco, San Francisco, CA, USA.
As we stand at the cusp of a transformative era in scholarly publishing, it is with great anticipation and excitement that we announce () will transition to an exclusively online format starting in 2025. This decision aligns with our commitment to sustainability, accessibility, and leveraging digital advancements to enhance the dissemination of vital public health research.
View Article and Find Full Text PDFPatient-Centric Approach to Personalized Electronic Medical Records via QR Code in Japan.
Interact J Med Res
December 2024
Life Science Laboratories, KDDI research atelier, KDDI Research, Inc, Fujimino, Saitama, Japan.
Government policies in the United States and the European Union promote standardization and value creation in the use of FAIR (findability, accessibility, interoperability, and reusability) data, which can enhance trust in digital health systems and is crucial for their success. Trust is built through elements such as FAIR data access, interoperability, and improved communication, which are essential for fostering innovation in digital health technologies. This Viewpoint aims to report on exploratory research demonstrating the feasibility of testing a patient-centric data flow model facilitating semantic interoperability on precision medical information.
View Article and Find Full Text PDFCentral command suite: futureproofing next-generation surgical environments to embrace the digital operating room.
Int J Comput Assist Radiol Surg
December 2024
Research Group MITI, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Paradigm shifts: exploring AI's influence on qualitative inquiry and analysis.
Front Res Metr Anal
December 2024
Teesside University International Business School, TU Online, Teesside University, Middlesbrough, United Kingdom.
Technology has mostly been embraced in qualitative research as it has not directly conflicted with qualitative methods' paradigmatic underpinnings. However, Artificial Intelligence (AI), and in particular the process of automating the analysis of qualitative research, has the potential to be in conflict with the assumptions of interpretivism. The short article aims to explore how AI technologies, such as Natural Language Processing (NLP), have started to be used to analyze qualitative data.
View Article and Find Full Text PDFHybrid Deep Learning-Based Enhanced Occlusion Segmentation in PICU Patient Monitoring.
IEEE Open J Eng Med Biol
November 2024
Biomedical Information Processing LabÉcole de Technologie Supérieure, University of Québec Montréal H3C 1K3 Canada.
Remote patient monitoring has emerged as a prominent non-invasive method, using digital technologies and computer vision (CV) to replace traditional invasive monitoring. While neonatal and pediatric departments embrace this approach, Pediatric Intensive Care Units (PICUs) face the challenge of occlusions hindering accurate image analysis and interpretation. In this study, we propose a hybrid approach to effectively segment common occlusions encountered in remote monitoring applications within PICUs.
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