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http://dx.doi.org/10.1097/CNJ.0000000000001330 | DOI Listing |
J Addict Nurs
August 2025
Brandy Mechling, PhD, RN, PMHCNS-BC, FNAP, University of North Carolina Wilmington, Wilmington, NC.
In the United States, approximately 20 million individuals, age 12 and older, have a substance use disorder (SUD), with an average age of first-time use at 13 years old. Evidence has shown that many SUDs begin in adolescence, and involvement with the legal system can ensue. Adolescents with first-time drug and alcohol arrests can be referred to an Adolescent Intervention Program (AIP) as an alternative to jailtime from the juvenile court system.
View Article and Find Full Text PDFJ Christ Nurs
September 2025
Professional and specialty nursing organizations (SNOs) develop position statements to offer practice guidance, amplify the views of nursing, educate consumers and decision makers, and encourage research. The Westberg Institute Research Committee, with representatives from other faith community nursing specialty organizations, has answered frequently asked practice questions by developing position statements using a rigorous process of statement development underpinned by topic exploration and synthesis of existing research and utilizing surveys to assess current practice. The processes for creating a position statement, Faith Community Nursing's Response to Inclusion, Diversity and Cultural Sensitivity, and revising Faith Community Nursing: Hands-On, Direct Care, and Specialized Care are presented.
View Article and Find Full Text PDFAm J Hosp Palliat Care
August 2025
Yale University School of Medicine, New Haven, CT, USA.
BackgroundMuslim patients have historically received aggressive end-of-life care, though palliative acceptance is growing. The factors that influence ICU (aggressive) vs ward (comfort-focused) deaths remain unclear, limiting value-concordant care.PurposeTo examine end-of-life care patterns and predictors of ICU vs ward death among Muslim patients, to guide culturally sensitive care.
View Article and Find Full Text PDFBioengineering (Basel)
July 2025
Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos 13566-590, Brazil.
The growing demand for accurate and efficient Chest X-Ray (CXR) interpretation has prompted the development of AI-driven systems to alleviate radiologist workload and reduce diagnostic variability. This paper introduces the Intelligent Humanized Radiology Analysis System (IHRAS), a modular framework that automates the end-to-end process of CXR analysis and report generation. IHRAS integrates four core components: (i) deep convolutional neural networks for multi-label classification of 14 thoracic conditions; (ii) Grad-CAM for spatial visualization of pathologies; (iii) SAR-Net for anatomical segmentation; and (iv) a large language model (DeepSeek-R1) guided by the CRISPE prompt engineering framework to generate structured diagnostic reports using SNOMED CT terminology.
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