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Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria.
Front Digit Health
January 2025
Department of Demography & Social Statistics, Federal University, Birnin-Kebbi, Kebbi State, Nigeria.
Background: Fertility preferences refer to the number of children an individual would like to have, regardless of any obstacles that may stand in the way of fulfilling their aspirations. Despite the creation and application of numerous interventions, the overall fertility rate in West African nations, particularly Nigeria, is still high at 5.3% according to 2018 Nigeria Demographic and Health Survey data.
View Article and Find Full Text PDFA 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 PDFRisk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy.
BMC Pregnancy Childbirth
January 2025
Jiaxing Maternity and Child Health Care Hospital, Jiaxing, Zhejiang, 314001, China.
Background: Intrahepatic cholestasis of pregnancy (ICP) is a liver disorder that occurs in the second and third trimesters of pregnancy and is associated with a significant risk of fetal complications, including premature birth and fetal death. In clinical practice, the diagnosis of ICP is predominantly based on the presence of pruritus in pregnant women and elevated serum total bile acid. However, this approach may result in missed or delayed diagnoses.
View Article and Find Full Text PDFError-driven upregulation of memory representations.
Commun Psychol
January 2025
Institute of Psychology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
Learning an association does not always succeed on the first attempt. Previous studies associated increased error signals in posterior medial frontal cortex with improved memory formation. However, the neurophysiological mechanisms that facilitate post-error learning remain poorly understood.
View Article and Find Full Text PDFOptimized convolutional neural network using African vulture optimization algorithm for the detection of exons.
Sci Rep
January 2025
Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still required to increase the identification accuracy of exons.
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