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Development, implementation, and evaluation of an innovative clinical trial operations training program for Africa (ClinOps).
BMC Med Educ
January 2025
Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University, P.O. Box 9086, Addis Ababa, Ethiopia.
Background: Africa's involvement in clinical trials remains very low. Although the crucial role of training initiatives in building clinical trial capacity in Africa has been documented, current efforts fall short as they lack alignment with local contexts. This study aimed to design, develop, implement, and evaluate an innovative clinical trial operations training program for Africa.
View Article and Find Full Text PDFOptimizing healthcare big data performance through regional computing.
Sci Rep
January 2025
Faculty of Resilience, Rabdan Academy, Abu Dhabi, United Arab Emirates.
The healthcare sector is experiencing a digital transformation propelled by the Internet of Medical Things (IOMT), real-time patient monitoring, robotic surgery, Electronic Health Records (EHR), medical imaging, and wearable technologies. This proliferation of digital tools generates vast quantities of healthcare data. Efficient and timely analysis of this data is critical for enhancing patient outcomes and optimizing care delivery.
View Article and Find Full Text PDFA modern, flexible cloud-based database and computing service for real-time analysis of vehicle emissions data.
Urban Inform
January 2025
IVL Swedish Environmental Research Institute LTD., PO Box 530 21, SE-400 14 Gothenburg, Sweden.
In response to the demand for advanced tools in environmental monitoring and policy formulation, this work leverages modern software and big data technologies to enhance novel road transport emissions research. This is achieved by making data and analysis tools more widely available and customisable so users can tailor outputs to their requirements. Through the novel combination of vehicle emissions remote sensing and cloud computing methodologies, these developments aim to reduce the barriers to understanding real-driving emissions (RDE) across urban environments.
View Article and Find Full Text PDFEnhanced detection of atrial fibrillation in single-lead electrocardiograms using a cloud-based artificial intelligence platform.
Heart Rhythm
January 2025
IDOVEN Research, Madrid, Spain; Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain; Centro de Investigación Biomédica en Red. Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain. Electronic address:
Background: Although smartphone-based devices have been developed to record 1-lead ECG, existing solutions for automatic atrial fibrillation (AF) detection often has poor positive predictive value.
Objective: This study aimed to validate a cloud-based deep learning platform for automatic AF detection in a large cohort of patients using 1-lead ECG records.
Methods: We analyzed 8,528 patients with 30-second ECG records from a single-lead handheld ECG device.
Artificial intelligence education in medical imaging: A scoping review.
J Med Imaging Radiat Sci
December 2024
Singapore Institute of Technology, 10 Dover Drive, 138683, Singapore.
Background: The rise of Artificial intelligence (AI) is reshaping healthcare, particularly in medical imaging. In this emerging field, clinical imaging personnel need proper training. However, formal AI education is lacking in medical curricula, coupled with a shortage of studies synthesising the availability of AI curricula tailored for clinical imaging personnel.
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