Biventricular pacing (BiVP) can increase cardiac output (CO) during acute failure of the left ventricle (LV) after cardiac surgery. This CO benefit is maximized by adjustment of atrioventricular (AVD) and interventricular (VVD) pacing delays. Real-time CO calculation could facilitate this optimization. Accordingly, we compared real-time automated analysis (AA) of CO with manual analysis (MA) in an animal model of pressure overload of the right ventricle (RV). In six anesthetized pigs, pacing leads were placed on the right atrium, RV, and LV. Complete heart block was induced with ethanol injection, and RV systolic pressure was doubled with a pulmonary artery snare. Atrioventricular pacing delay was varied over seven common values and VVD over nine, in random sequence. Two LV pacing sites (LVPS) were also tested. Aortic flow velocity, measured by ultrasonic flow probe, was integrated by AA and MA to calculate CO. Interexaminer Reliability Coefficient (IRC) was determined by Analysis of Variance (ANOVA) for two 10-second runs in each animal. Cardiac output-AVD and CO-VVD relations were similar for AA and MA. Interexaminer Reliability Coefficients were 0.997 and 0.994 for MA vs. AA. Automated analysis was available in real-time. Manual analysis was delayed at 2 hours or more. Automated analysis merits development for real-time optimization of intraoperative BiVP.
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http://dx.doi.org/10.1097/MAT.0b013e3181cf882a | DOI Listing |
Pediatr Surg Int
January 2025
Department of Pediatric Surgery, First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Objective: To review and compare robot-assisted ipsilateral ureteroureterostomy (RALUU) and laparoscopic ipsilateral uretero-ureterostomy (LUU) in terms of efficacy and outcomes.
Methods: Clinical data of 65 children with complete renal ureteral duplication deformity admitted to the First Affiliated Hospital of Zhengzhou University from January 2015 to December 2022 were collected. Among these, 42 patients underwent laparoscopic ureteroureterostomy (LUU), designated as the LUU group, while 23 patients received robot-assisted laparoscopic ureteroureterostomy (RALUU), designated as the RALUU group.
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.
Sci Rep
January 2025
Xingtai Naknor Technology Co., Ltd, Xingtai, 054000, China.
The heating oil circuit plays an essential role in the heating calendering roller for the lithium battery pole piece. To achieve the optimization of the heating oil circuit, a fluid-thermal-structural coupling method and a multi-objective optimization procedure are proposed to obtain the optimal solution. A fluid-thermal-structural coupling flowchart based on the numerical modeling for the calendering roller temperature distribution is created to automate the analysis processes in the optimization iteration.
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January 2025
School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India.
Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pandemic, many people were suffering from lung disorders, which elevated the demand for mechanical ventilators. The handling of mechanical ventilators is to be done under the assistance of trained professionals and demands the selection of ideal parameters.
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January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
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