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AI-derived automated quantification of cardiac chambers and myocardium from non-contrast CT: Prediction of major adverse cardiovascular events in asymptomatic subjects.
Atherosclerosis
December 2024
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Electronic address:
Background And Aims: The significance of left ventricular mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of artificial intelligence-enabled multi-chamber cardiac volumetry from non-contrast CT for long-term risk stratification in asymptomatic subjects without known coronary artery disease.
Methods: Our study included 2022 asymptomatic individuals (55.
Computed tomography-based fully automated artificial intelligence model to predict extrapancreatic perineural invasion in pancreatic ductal adenocarcinoma.
Int J Surg
December 2024
Department of Radiology, Changhai Hospital.
Background: Extrapancreatic perineural invasion (EPNI) increases the risk of postoperative recurrence in pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop and validate a computed tomography (CT)-based, fully automated preoperative artificial intelligence (AI) model to predict EPNI in patients with PDAC.
Methods: The authors retrospectively enrolled 1065 patients from two Shanghai hospitals between June 2014 and April 2023.
Machine Condition Monitoring System Based on Edge Computing Technology.
Sensors (Basel)
December 2024
Institute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, Slovakia.
The core of this publication is the design of a system for evaluating the condition of production equipment and machines by monitoring selected parameters of the production process with an additional sensor subsystem. The main positive of the design is the processing of data from the sensor layer using artificial intelligence (AI) and expert systems (ESs) with the use of edge computing (EC). Sensor information is processed directly at the sensor level on the monitored equipment, and the results of the individual subsystems are stored in the form of triggers in a database for use in the predictive maintenance process.
View Article and Find Full Text PDFChallenges in pregnancy and lactation among surgical residents and attendings: A systematic review.
Surgery
January 2025
Department of Gastro-Intestinal Surgery, Ghent University Hospital, Ghent, Belgium. Electronic address:
Background: With more women entering surgical training, barriers concerning pregnancy and breastfeeding are pertinent issues that have not been addressed adequately in a specialty with more men. An increasing body of evidence for the consequences of these challenges is emerging but has not been reviewed thoroughly. This study aims to provide a comprehensive review of the physical, emotional, and practical challenges of pregnancy and breastfeeding during surgical training and career and to elucidate the main difficulties and barriers female surgeons experience.
View Article and Find Full Text PDFComputational pathology applied to clinical colorectal cancer cohorts identifies immune and endothelial cell spatial patterns predictive of outcome.
J Pathol
February 2025
Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.
Colorectal cancer (CRC) is a histologically heterogeneous disease with variable clinical outcome. The role the tumour microenvironment (TME) plays in determining tumour progression is complex and not fully understood. To improve our understanding, it is critical that the TME is studied systematically within clinically annotated patient cohorts with long-term follow-up.
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