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http://dx.doi.org/10.7861/clinmed.20-2-s62 | DOI Listing |
Arch Gynecol Obstet
January 2025
Frauenklinik Kantonsspital St. Gallen, St. Gallen, Switzerland.
Background: There is frequent academic exchange between Switzerland, Germany and Austria, facilitated by the common language. Additionally, the postgraduate training curricula in obstetrics and gynecology show some similarities. We aimed to compare self-perceived level of ability, availability of simulation training and teaching and feedback culture among residents in obstetrics and gynecology in Switzerland, Germany, and Austria.
View Article and Find Full Text PDFMil Med
January 2025
Combat Paramedic Program, U.S. Army MedCoE, JBSA Fort Sam Houston, TX 78234, USA.
The combat medic (68W) will play a critical role in medical operations in the event of future large-scale combat operations (LSCOs). However, the combat medic is largely not prepared for LSCOs. The revised Medical Education and Demonstration of Individual Competence (TC 8-800) state 68Ws much be able to provide advanced airway and trauma management, medication administration, and advanced casualty movement.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Anaesthesiology and Intensive Care, Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia.
Regional anaesthesia has seen a resurgence of sorts since the widespread advent of ultrasound into clinical practice. The ability to access hitherto inaccessible nerves and fascial planes in the human body whilst ensuring visualisation of the needle tip during block performance has opened the proverbial floodgates leading to its widespread adoption, further supported by a growing body of evidence for its many benefits in a patient's perioperative journey and pain management. The concomitant advancement of technology and the development of powerful simulation and artificial intelligence tools has given a much-needed impetus towards improving training and safe practice in regional anaesthesia.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Transportation, Shandong University of Science and Technology, Qingdao 266590, China.
To address the problems that exist in the target detection of vehicle-mounted visual sensors in foggy environments, a vehicle target detection method based on an improved YOLOX network is proposed. Firstly, to address the issue of vehicle target feature loss in foggy traffic scene images, specific characteristics of fog-affected imagery are integrated into the network training process. This not only augments the training data but also improves the robustness of the network in foggy environments.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Automotive Power Train and Electronics, Hubei University of Automotive Technology, Shiyan 442002, China.
Autonomous driving has demonstrated impressive driving capabilities, with behavior decision-making playing a crucial role as a bridge between perception and control. Imitation Learning (IL) and Reinforcement Learning (RL) have introduced innovative approaches to behavior decision-making in autonomous driving, but challenges remain. On one hand, RL's policy networks often lack sufficient reasoning ability to make optimal decisions in highly complex and stochastic environments.
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