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Evaluation of machine learning techniques for real-time prediction of implanted lower limb mechanics.
Front Bioeng Biotechnol
January 2025
Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Introduction: Accurate prediction of knee biomechanics during total knee replacement (TKR) surgery is crucial for optimal outcomes. This study investigates the application of machine learning (ML) techniques for real-time prediction of knee joint mechanics.
Methods: A validated finite element (FE) model of the lower limb was used to generate a dataset of knee joint kinematics, kinetics, and contact mechanics.
Diagnosis of traumatic liver injury on computed tomography using machine learning algorithms and radiomics features: The role of artificial intelligence for rapid diagnosis in emergency rooms.
J Res Med Sci
December 2024
Department of Biostatistics, Student Research Committee, University of Medical Sciences, Kermanshah, Iran.
Background: The initial assessment of trauma is a time-consuming and challenging task. The purpose of this research is to examine the diagnostic effectiveness and usefulness of machine learning models paired with radiomics features to identify blunt traumatic liver injury in abdominal computed tomography (CT) images.
Materials And Methods: In this study, 600 CT scan images of people with mild and severe liver damage due to trauma and healthy people were collected from the Kaggle dataset.
Avoiding never events in orthopaedics theatres: a quality improvement project.
BMJ Open Qual
January 2025
Trauma & Orthopaedics, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK.
Never events in the operating room are a surgeon's nightmare, with an incidence rate of 54%. These events are highly stressful for theatre staff and significantly compromise patient safety. The aim of this project is to avoid never events in trauma and orthopaedic theatres by ensuring that theatre staff adhere to the surgical pause and imaging pause protocols through regular audits.
View Article and Find Full Text PDFAnalyzing and mitigating the risks of patient harm during operating room to intensive care unit patient handoffs.
Int J Qual Health Care
January 2025
Faculdade de Medicina, Universidade de São Paulo (USP), Av. Dr. Arnaldo, 455 - Sala 4107, São Paulo, São Paulo 01246-903, Brazil.
Patients continue to suffer from preventable harm and uneven quality outcomes. Reliable clinical outcomes depend on the quality of robust administrative systems and reliable support processes. Critically ill patient handoffs from the operating room (OR) to the intensive care unit (ICU) are known to be high-risk events.
View Article and Find Full Text PDFThe quality of orientation for newly hired nurses in acute care settings in a university hospital: A cross-sectional study.
Appl Nurs Res
February 2025
University of Helsinki and Helsinki University Hospital, Nursing Research Center, Tukholmankatu 8F, P.O. Box 442, FIN-00029 HUS, Finland; Lovisenberg Diaconal University College, Oslo, Norway. Electronic address:
Aims: This study aims to describe how newly hired nurses assess the quality of the orientation in acute care settings in a university hospital.
Background: Orientation for newly hired nurses in acute care settings, where special competence, ability to collaborate with different professional groups, and wide technical and technological skills are required, is crucial to ensure patient safety and high-quality standards in nursing care.
Methods: A cross-sectional study design was applied.
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