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Timing based clustering of childhood BMI trajectories reveals differential maturational patterns; Study in the Northern Finland Birth Cohorts 1966 and 1986.
Int J Obes (Lond)
January 2025
Research Unit of Population Health, University of Oulu, Oulu, Finland.
Background/objectives: Children's biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI.
View Article and Find Full Text PDFAssessing the global dynamics of Nipah infection under vaccination and treatment: A novel computational modeling approach.
PLoS One
January 2025
Department of Mathematics, University of Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan.
In biology and life sciences, fractal theory and fractional calculus have significant applications in simulating and understanding complex problems. In this paper, a compartmental model employing Caputo-type fractional and fractal-fractional operators is presented to analyze Nipah virus (NiV) dynamics and transmission. Initially, the model includes nine nonlinear ordinary differential equations that consider viral concentration, flying fox, and human populations simultaneously.
View Article and Find Full Text PDFEutherianCoP. An integrated biotic and climate database for conservation paleobiology based on eutherian mammals.
Sci Data
January 2025
DiSTAR, University of Naples "Federico II", 80126, via Vicinale Cupa Cintia 26, Naples, Italy.
We present a new database, EutherianCoP, of fossil mammals which lived globally from the Late Pleistocene to the Holocene. The database includes 13,972 fossil occurrences of 786 extant or recently extinct placental mammal species, plus 155,198 current occurrences for those of them which survived to the present. The occurrences are correlated with radiometric age information.
View Article and Find Full Text PDFSemi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data.
J Magn Reson Imaging
January 2025
Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway.
Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.
Purpose: This work tests the viability of semi-supervision for brain metastases segmentation.
GQEO: Nearest neighbor graph-based generalized quadrilateral element oversampling for class-imbalance problem.
Neural Netw
December 2024
College of Science, North China University of Science and Technology, Tangshan, 063210, China. Electronic address:
The class imbalance problem is one of the difficult factors affecting the performance of traditional classifiers. The oversampling technique is the most common way to solve the class imbalance problem. They alleviate the performance impact of the class imbalance problem on traditional machine learning by augmenting minority instance feature representation.
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