Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1136/emermed-2018-208117 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Two step approach for detecting and segmenting the second mesiobuccal canal of maxillary first molars on cone beam computed tomography (CBCT) images via artificial intelligence.
BMC Oral Health
September 2025
Oral and Maxillofacial Radiology Department, Cairo university, Cairo, Egypt.
Aim: The purpose of this study was to assess the accuracy of a customized deep learning model based on CNN and U-Net for detecting and segmenting the second mesiobuccal canal (MB2) of maxillary first molar teeth on cone beam computed tomography (CBCT) scans.
Methodology: CBCT scans of 37 patients were imported into 3D slicer software to crop and segment the canals of the mesiobuccal (MB) root of the maxillary first molar. The annotated data were divided into two groups: 80% for training and validation and 20% for testing.
Optimising the educational utility of live tissue training in trauma surgery.
BMC Med Educ
September 2025
Department of Learning, Informatics, Management & Ethics (LIME) Widerströmska huset, Karolinska Institutet, Stockholm, Sweden.
Background: Live tissue training (LTT) refers to the use of live anaesthetised animals for the purpose of medical education. It is a type of simulation training that is contentious, and there is an ethical imperative for educators to justify the use of animals. This should include scrutinising educational practices.
View Article and Find Full Text PDFBarriers and facilitators of the implementation for the antimicrobial Social Norm Feedback (SNF) intervention strategy in primary care institutions: a qualitative study based on the Consolidated Framework for Implementation Research (CFIR).
Antimicrob Resist Infect Control
September 2025
School of Medicine and Health Management, Guizhou Province, Guizhou Medical University, GUI'an New District, 6 Ankang Avenue, Guiyang, People's Republic of China.
Background: Although current evidence supports the effectiveness of social norm feedback (SNF) interventions, their sustained integration into primary care remains limited. Drawing on the elements of the antimicrobial SNF intervention strategy identified through the Delphi-based evidence applicability evaluation, this study aims to explore the barriers and facilitators to its implementation in primary care institutions, thereby informing future optimization.
Methods: Based on the five domains of the Consolidated Framework for Implementation Research (CFIR), we developed semi-structured interview and focus group discussion guides.
Correction: An explainable machine learning model for early warning of hypertensive and hypotensive anomalies in maintenance hemodialysis patients.
BMC Nephrol
September 2025
School of Computer Science and Technology, Guangxi University of Science and Technology, Liuzhou, China.
Use of artificial intelligence for classification of fractures around the elbow in adults according to the 2018 AO/OTA classification system.
BMC Musculoskelet Disord
September 2025
Department of Clinical Sciences at Danderyds Hospital, Department of Orthopedic Surgery, Karolinska Institutet, Stockholm, 182 88, Sweden.
Background: This study evaluates the accuracy of an Artificial Intelligence (AI) system, specifically a convolutional neural network (CNN), in classifying elbow fractures using the detailed 2018 AO/OTA fracture classification system.
Methods: A retrospective analysis of 5,367 radiograph exams visualizing the elbow from adult patients (2002-2016) was conducted using a deep neural network. Radiographs were manually categorized according to the 2018 AO/OTA system by orthopedic surgeons.