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Diagnostic value of the MZXBTCH scoring system for acute complex appendicitis.
Sci Rep
January 2025
Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, No. 168 Litang Road, Changping District, Beijing, 102218, China.
The objective of this study was to develop a novel scoring model, assess its diagnostic value for complex appendicitis, and compare it with existing scoring systems. A total of 1,241 patients with acute appendicitis were included, comprising 868 patients in the modeling group (mean age, 35.6 ± 14.
View Article and Find Full Text PDFArtificial intelligence for body composition assessment focusing on sarcopenia.
Sci Rep
January 2025
Division of Cancer Systems Biology, Aichi Cancer Center Research Institute, Nagoya, Aichi, Japan.
This study aimed to address the limitations of conventional methods for measuring skeletal muscle mass for sarcopenia diagnosis by introducing an artificial intelligence (AI) system for direct computed tomography (CT) analysis. The primary focus was on enhancing simplicity, reproducibility, and convenience, and assessing the accuracy and speed of AI compared with conventional methods. A cohort of 3096 cases undergoing CT imaging up to the third lumbar (L3) level between 2011 and 2021 were included.
View Article and Find Full Text PDFAccuracy of body weight estimation for fetuses with congenital diaphragmatic hernia.
Congenit Anom (Kyoto)
January 2025
Department of Neonatology, Hyogo Prefectural Kobe Children's Hospital, Kobe, Hyogo, Japan.
Genomic Selection and WssGWAS of Sheep Body Weight and Milk Yield: Imputing Low-Coverage Sequencing Data with Similar Genetic Background Panels.
J Dairy Sci
January 2025
College of Animal Science and Technology, Northwest A&F University, 22 nt, Xinong Road, Yangling, Shaanxi, China. Electronic address:
Low-coverage whole-genome sequencing (LcWGS), a cost-effective genotyping method, offers greater flexibility in variant detection than does single-nucleotide polymorphism (SNP) chips. However, to our knowledge, no studies have explored the application of LcWGS in sheep. This study aimed to evaluate the feasibility of implementing LcWGS and genotype imputation and assess their applicability in genomic studies of body weight and milk yield in sheep.
View Article and Find Full Text PDFMultilabel segmentation and analysis of skeletal muscle and adipose tissue in routine abdominal CT scans.
Comput Biol Med
January 2025
Department of Simulation and Graphics, Faculty of Computer Science, University of Magdeburg, Universitätsplatz 2 39106, Magdeburg, Germany; Department of Computational Medicine, Ilmenau University of Technology, Germany.
Purpose: This paper presents a deep learning-based multi-label segmentation network that extracts a total of three separate adipose tissues and five different muscle tissues in CT slices of the third lumbar vertebra and additionally improves the segmentation of the intermuscular fat.
Method: Based on a self-created data set of 130 patients, an extended Unet structure was trained and evaluated with the help of Dice score, IoU and Pixel Accuracy. In addition, the interobserver variability for the decision between ground truth and post-processed segmentation was calculated to illustrate the relevance in everyday clinical practice.
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