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Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.
Radiol Med
January 2025
Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Purpose: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Methods: On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard.
An involvement of a new zinc finger protein PbrZFP719 into pear self-incompatibility reaction.
Plant Cell Rep
January 2025
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Saya Institute of Nanjing Agricultural University, Nanjing Agricultural University, Nanjing, 211800, China.
This study indicated that the CCHC-type zinc finger protein PbrZFP719 involves into self-incompatibility by affecting the levels of reactive oxygen species and cellulose content at the tips of pollen tubes. S-RNase-based self-incompatibility (SI) facilitates cross-pollination and prevents self-pollination, which in turn increases the costs associated with artificial pollination in fruit crops. Self S-RNase exerts its inhibitory effects on pollen tube growth by altering cell structures and components, including reactive oxygen species (ROS) level and cellulose content.
View Article and Find Full Text PDFEpidemiology of invasive candidiasis before and during the COVID-19 pandemic at a hospital in southeastern Brazil.
J Infect Dev Ctries
December 2024
Department of Internal Medicine, Faculty of Medical Sciences, State University of Campinas, Campinas, Brazil.
Introduction: Invasive candidiasis is an important cause of nosocomial infection and recent studies have shown an increase in the number of cases during the coronavirus disease 2019 (COVID-19) pandemic. The present study aimed to evaluate the epidemiology and incidence of invasive candidiasis before and during the COVID-19 pandemic at a reference tertiary hospital in Brazil.
Methodology: A retrospective observational study was performed with 148 patients infected with Candida spp.
Application of artificial intelligence in nursing practice: a qualitative study of Jordanian nurses' perspectives.
BMC Nurs
January 2025
Nursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar.
Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.
View Article and Find Full Text PDFAdjusting on-scene CPR duration based on transport time interval in out-of-hospital cardiac arrest: a nationwide multicenter study.
Sci Rep
January 2025
Division of Critical Care Medicine, Department of Emergency Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong-si, Gyeonggi-do, Republic of Korea.
The optimal duration of on-scene cardiopulmonary resuscitation (CPR) for out-of-hospital cardiac arrest (OHCA) patients remains uncertain. Determining this critical time period requires outweighing the potential risks associated with intra-arrest transport while minimizing delays in accessing definitive hospital-based treatments. This study evaluated the association between on-scene CPR duration and 30-day neurologically favorable survival based on the transport time interval (TTI) in patients with OHCA.
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