Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) Kansas worked with 10 Kansas counties from November 2020 through June 2022 to form local health equity action teams (LHEATs), develop COVID-19 testing strategies, foster communication about COVID-19, and share best practices through a learning collaborative. Participating counties documented 693 distinct COVID-19 testing and 178 communication activities. Although the intervention was not associated with changes in the proportion of positive COVID-19 tests, LHEATs in the learning collaborative implemented new testing strategies and responded to emerging COVID-19 challenges. (. 2024;114(11):1202-1206. https://doi.org/10.2105/AJPH.2024.307771).
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http://dx.doi.org/10.2105/AJPH.2024.307771 | DOI Listing |
PLoS One
January 2025
North China Institute of Aerospace Engineering, Langfang, China.
As the global economy expands, waterway transportation has become increasingly crucial to the logistics sector. This growth presents both significant challenges and opportunities for enhancing the accuracy of ship detection and tracking through the application of artificial intelligence. This article introduces a multi-object tracking system designed for unmanned aerial vehicles (UAVs), utilizing the YOLOv7 and Deep SORT algorithms for detection and tracking, respectively.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Learning and Capacity Development Unit, Health Emergencies Programme, World Health Organization, Geneva, Switzerland.
Background: The COVID-19 pandemic demonstrated the global need for accessible content to rapidly train health care workers during health emergencies. The massive open access online course (MOOC) format is a broadly embraced strategy for widespread dissemination of trainings. Yet, barriers associated with technology access, language, and cultural context limit the use of MOOCs, particularly in lower-resource communities.
View Article and Find Full Text PDFBMJ
January 2025
Collaborative Intelligence, World Health Organization, Health Emergencies Programme, Berlin, Germany.
Curr Res Transl Med
January 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.
View Article and Find Full Text PDFEur J Case Rep Intern Med
November 2024
Department of Lung Diseases and Thoracic Surgery, Pauls Stradins Clinical University Hospital, Riga, Latvia.
Background: Clinically amyopathic dermatomyositis (CADM) is a rare subtype of idiopathic inflammatory myositis often linked with the presence of autoantibodies targeting melanoma differentiation-associated protein 5 (MDA5). Patients with CADM are at increased risk of developing rapidly progressing interstitial lung disease, which significantly increases both morbidity and mortality compared to other forms of inflammatory myopathies. While there is no standardized treatment regimen, current therapeutic strategies are generally focused on combination immunosuppressive therapies.
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