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Study Design: This paper presents a description of a conceptual framework and methodology that is applicable to the manuscripts that comprise this focus issue.
Objectives: Our goal is to present a conceptual framework which is relied upon to better understand the processes through which surgeons make therapeutic decisions around how to treat thoracolumbar burst fractures (TL) fractures.
Methods: We will describe the methodology used in the AO Spine TL A3/4 Study prospective observational study and how the radiographs collected for this study were utilized to study the relationships between various variables that factor into surgeon decision making.
Results: With 22 expert spine trauma surgeons analyzing the acute CT scans of 183 patients with TL fractures we were able to perform pairwise analyses, look at reliability and correlations between responses and develop frequency tables, and regression models to assess the relationships and interactions between variables. We also used machine learning to develop decision trees.
Conclusions: This paper outlines the overall methodological elements that are common to the subsequent papers in this focus issue.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10867530 | PMC |
http://dx.doi.org/10.1177/21925682231210183 | DOI Listing |
Glob Ment Health (Camb)
July 2025
School of Social Sciences, College of Humanities, Arts, and Social Sciences, Nanyang Technological University, Singapore.
The global prevalence of mental health disorders among youths aged 15 to 24 is a significant public health concern. This systematic review aimed to explore global strategies for promoting mental well-being and addressing mental health challenges within this demographic, as defined by the World Health Organization. A comprehensive search of electronic scientific databases was conducted on November 1, 2023, yielding 43 studies with a total of 29,581 participants published between 2008 and 2023 that examined mental health interventions targeting youth.
View Article and Find Full Text PDFRisk Manag Healthc Policy
September 2025
Khalifa University of Science & Technology, Department of Management Science & Engineering, Abu Dhabi, 127788, United Arab Emirates.
Central Line-Associated Bloodstream Infections (CLABSI) pose significant challenges in healthcare systems globally, contributing to increased morbidity, mortality, and healthcare costs. As healthcare organizations strive to improve patient safety and quality of care, Artificial Intelligence (AI) presents considerable promise in the prevention, detection, and management of CLABSI. This paper proposes a conceptual framework that integrates AI within healthcare systems, aligning technological innovations with human workflows, system design, and risk management strategies.
View Article and Find Full Text PDFPatterns (N Y)
July 2025
Cedars-Sinai Medical Center, Los Angeles, CA, USA.
The tree-based pipeline optimization tool (TPOT) is one of the earliest automated machine learning (ML) frameworks developed for optimizing ML pipelines, with an emphasis on addressing the complexities of biomedical research. TPOT uses genetic programming to explore a diverse space of pipeline structures and hyperparameter configurations in search of optimal pipelines. Here, we provide a comparative overview of the conceptual similarities and implementation differences between the previous and latest versions of TPOT, focusing on two key aspects: (1) the representation of ML pipelines and (2) the underlying algorithm driving pipeline optimization.
View Article and Find Full Text PDFHealth Policy Plan
September 2025
Regional Emergency Director, WHO Health Emergencies Department, WHO South-East Asian Regional Office, New Delhi, India.
Zoonotic influenzas are major, ongoing public health policy challenge, not the least because of the importance of functional multisector partnerships (MSPs) for their prevention and control. However, despite years of investment in developing them, many countries have found multisectoral approaches, such as One Health, difficult to operationalise at national and sub national levels. One explanation for the lack of uptake is the limited nature of guidance on the design and adaptation of MSPs that consider local institutional dynamics.
View Article and Find Full Text PDFNat Microbiol
September 2025
Joan and Sanford I. Weill Department of Medicine, Gastroenterology and Hepatology Division, Weill Cornell Medicine, New York, NY, USA.
Microbial influence on cancer development and therapeutic response is a growing area of cancer research. Although it is known that microorganisms can colonize certain tissues and contribute to tumour initiation, the use of deep sequencing technologies and computational pipelines has led to reports of multi-kingdom microbial communities in a growing list of cancer types. This has prompted discussions on the role and scope of microbial presence in cancer, while raising the possibility of microbiome-based diagnostic, prognostic and therapeutic tools.
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