[This corrects the article DOI: 10.1371/journal.pone.0215571.].
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223796 | PLOS |
BMC Oral Health
January 2025
Department of Clinical Dentistry, Faculty of Medicine, University of Bergen, Bergen, Norway.
Background: In the last years, artificial intelligence (AI) has contributed to improving healthcare including dentistry. The objective of this study was to develop a machine learning (ML) model for early childhood caries (ECC) prediction by identifying crucial health behaviours within mother-child pairs.
Methods: For the analysis, we utilized a representative sample of 724 mothers with children under six years in Bangladesh.
Crim Behav Ment Health
January 2025
Institute of Psychology, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany.
Background: This article is dedicated to David Farrington who was a giant in criminology and, in particular, a pioneer in studying developmental pathways of delinquent and antisocial behaviour. Numerous studies followed his work. Systematic reviews of his and others' research described between two and seven (mainly 3-5) trajectories.
View Article and Find Full Text PDFEur Respir Rev
January 2025
Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
Introduction: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.
Methods: 10 databases were searched.
Background: Childhood sleep problems are common and impact physical and emotional health. Prior work suggests that prenatal maternal depression and anxiety associate with disturbed child sleep in infancy. The current study evaluated whether these same associations extend to children at 3 years of age, and if so, whether the timing of symptoms in pregnancy is relevant.
View Article and Find Full Text PDFAnn Pediatr Endocrinol Metab
December 2024
Department of Pediatrics, Seoul National University Children's Hospital, Seoul, Korea.
Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated.
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