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A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks.
BioData Min
January 2025
Department of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia.
Background: This study employs a LSTM-FC neural networks to address the critical public health issue of child undernutrition in Ethiopia. By employing this method, the study aims classify children's nutritional status and predict transitions between different undernutrition states over time. This analysis is based on longitudinal data extracted from the Young Lives cohort study, which tracked 1,997 Ethiopian children across five survey rounds conducted from 2002 to 2016.
View Article and Find Full Text PDFKey performance indicators in emergency department simulation: a scoping review.
Scand J Trauma Resusc Emerg Med
January 2025
Health Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Background: One way to measure emergency department (ED) performance is using key performance indicators (KPIs). Thus, identifying reliable KPIs can be critical in appraising ED performance. This study aims to introduce and classify the KPIs related to ED in simulations through the Balanced Scorecard (BSC) framework.
View Article and Find Full Text PDFComprehensive analysis of the succinylome in Vero cells infected with peste des petits ruminants virus Nigeria 75/1 vaccine strain.
BMC Vet Res
January 2025
State Key Laboratory for Animal Disease Control and Prevention, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Xujiaping 1, Yanchangpu, Chengguan District, Lanzhou, 730046, Gansu, China.
Background: Peste des petits ruminants virus (PPRV) is currently the only member of the Morbillivirus caprinae species within the genus Morbillivirus of the family Paramyoxviridae. PPRV causes a highly contagious disease in small ruminants, especially goats and sheep. Succinylation is a newly identified and conserved modification and plays an important role in host cell response to pathogen infection.
View Article and Find Full Text PDFBenefits of the Global Integration Method (Método de Integração Global - MIG) in functional priorities of parents of Brazilian children and adolescents with autism spectrum disorder.
BMC Pediatr
January 2025
Institute of Neurodevelopment, Cognition, and Inclusive Education (INCEI), Ribeirão das Neves, Belo Horizonte, MG, Brazil.
Background: Understanding the priorities of parents of children and adolescents with autism spectrum disorder (ASD) is crucial for implementing evidence-based programs. This study aims to identify the functional priorities of parents of Brazilian children and adolescents with ASD, analyze variations in priorities according to the levels of support and age groups of the participants, and categorize the goals according to the categories of the International Classification of Functioning, Disability, and Health (ICF). Additionally, this study aimed to evaluate changes in parents' performance and satisfaction with functional priorities after intervention with the Global Integration Method (Métodode Integração Global - MIG).
View Article and Find Full Text PDFIdentification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study.
BMC Cancer
January 2025
Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, 1 Xueyuan Road, Fujian, 350108, China.
Objective: This study aims to identify potential lipid biomarkers and metabolic pathways associated with oral cancer (OC). Then to establish and evaluate disease classification models capable of distinguishing OC patients from healthy controls.
Methods: A total of 41 OC patients and 41 controls were recruited from a hospital in Southeast China to examine the serum lipidomics by Ultra-high Performance Liquid Chromatography Q Exactive Mass Spectrometry (UHPLC-QE-MS).
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