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The Relationship Between Body Mass Index and Peripheral Artery Disease: Insights from the National Health and Nutrition Examination Survey and Mendelian Randomization Analysis.
J Surg Res
January 2025
School of Medicine, Tongji University, Shanghai, China; Department of Health Statistics, Navy Medical University, Shanghai, China. Electronic address:
Introduction: Body mass index (BMI) has been implicated in various cardiovascular conditions, but its association with peripheral artery disease (PAD) in both real-world and genetic studies have been contentious and debated.
Methods: This study enrolled 6707 individuals from the National Health and Nutrition Examination Survey database to investigate the association between BMI and the risk of PAD. The weighted logistic regression, restricted cubic spline, and subgroup analysis were performed using real-world data.
Automated detection of traumatic bleeding in CT images using 3D U-Net# and multi-organ segmentation.
Biomed Phys Eng Express
January 2025
Chiba University Center for Frontier Medical Engineering, 1-33 Yayoi-cho, Inage-ku, Chiba, Chiba, 263-8522, JAPAN.
Traumatic injury remains a leading cause of death worldwide, with traumatic bleeding being one of its most critical and fatal consequences. The use of whole-body computed tomography (WBCT) in trauma management has rapidly expanded. However, interpreting WBCT images within the limited time available before treatment is particularly challenging for acute care physicians.
View Article and Find Full Text PDFThe Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.
J Med Internet Res
January 2025
School of Business, Innovation and Sustainability, Halmstad University, Halmstad, Sweden.
Background: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide support in several domains of mental health, including early detection, diagnostics, treatment, and self-care. The use of AI systems in care flows faces several challenges in relation to decision-making support, stemming from technology, end-user, and organizational perspectives with the AI disruption of care processes.
View Article and Find Full Text PDFEffect of Multimodal App-Based Interventions on Glycemic Control in Patients With Type 2 Diabetes: Systematic Review and Meta-Analysis.
J Med Internet Res
January 2025
Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Background: Digital technologies for type 2 diabetes mellitus (T2DM) care hold great potential to improve patients' health in the long term. Only a subset of telemedicine offerings are digital interventions that meet the criteria for prescribable digitale Gesundheitsanwendung (digital health apps; DiGAs) in Germany. Digital treatments further provide vast amounts of patient data that are important to generate evidence.
View Article and Find Full Text PDFAI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.
J Med Internet Res
January 2025
Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
Background: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection remains challenging due to its insidious symptoms. Current diagnostic methods, including clinical assessments and laboratory tests, frequently lack the speed and specificity needed for timely intervention, particularly in vulnerable populations such as older adults, intensive care unit (ICU) patients, and those with compromised immune systems.
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