The international journal of cardiovascular imaging
Dec 27, 2023
The existing multilabel X-Ray image learning tasks generally contain much information on pathology co-occurrence and interdependency, which is very important for clinical diagnosis. However, the challenging part of this subject is to accurately diagn...
Nutrition (Burbank, Los Angeles County, Calif.)
Dec 24, 2023
OBJECTIVES: This study combined two novel approaches in oncology patient outcome predictions-body composition and radiomic features analysis. The aim of this study was to validate whether automatically extracted muscle and adipose tissue radiomic fea...
Journal of laparoendoscopic & advanced surgical techniques. Part A
Dec 21, 2023
To determine the perioperative quality assessment results and learning curves for robot-assisted anatomical lung resection. We analyzed the data of the initial 400 patients who underwent lobectomies or segmentectomies by 1 surgeon from January 2020...
Journal of computer assisted tomography
Dec 18, 2023
OBJECTIVE: The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysem...
Artificial intelligence/machine learning tools are being created for use in pathology. Some examples related to lung pathology include acid-fast stain evaluation, programmed death ligand-1 (PDL-1) interpretation, evaluating histologic patterns of non...
. Deep learning networks such as convolutional neural networks (CNN) and Transformer have shown excellent performance on the task of medical image segmentation, however, the usual problem with medical images is the lack of large-scale, high-quality p...
OBJECTIVES: Prolonged air leak (PAL) is a common complication of lung resection. Research on predictors of PAL using a digital drainage system (DDS) remains insufficient. In this study, we investigated the predictive factors of PAL to establish a nov...
Biomedical physics & engineering express
Dec 8, 2023
Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs...
BACKGROUND: Deep learning in medical applications is limited due to the low availability of large labeled, annotated, or segmented training datasets. With the insufficient data available for model training comes the inability of these networks to lea...