Latest AI and machine learning research in pediatrics for healthcare professionals.
Background: Pediatric dilated cardiomyopathy (DCM) is a rare, progressive heart disease with variable outcomes that range from recovery to heart transplantation. To date, there are no prognostic biomarkers for children with DCM. Identifying circulating biomarkers that are associated with clinical outcomes is critical for personalized management. Methods: miRNAs were identified by RNA-seq, whereas ...
Advances in social media data dissemination enable the provision of real-time information during a crisis. The information comes from different classes, such as infrastructure damages, persons missing or stranded in the affected zone, etc. Existing methods attempted to classify text and images into various humanitarian categories, but their decision-making process remains largely opaque, which aff...
Raman spectroscopy is a promising tool for microbial identification, yet its implementation in microbiology and clinical workflow is still restricted ...
HER2 heterogeneity and reversible phenotypic plasticity play a central role in breast cancer progression and therapeutic resistance, yet how their int...
Mental health related problems in adolescents are not always properly evaluated because of incomplete evaluation methods that do not combine biologica...
Background Placental dysfunction remains a leading cause of stillbirth and neonatal morbidity, yet current monitoring tools provide only indirect and ...
Background: Previous research has shown that radiomics-based machine learning models are promising precision medicine tools for lesion-level predictio...
Predicting hospital outcomes for patients with severe acute respiratory infections is critical for risk stratification and resource planning, yet hete...
Background Artificial intelligence (AI) is increasingly being integrated into healthcare systems, with growing applications in clinical decision suppo...
Monitoring fish growth behavior provides relevant information about fish health in aquaculture and home aquariums. Yet, monitoring fish sizes poses di...
Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prenatal detection remains challenging due to the scarc...
This study presents dAMN, a hybrid neural-mechanistic model that integrates neural networks with genome-scale dynamic flux balance analysis (dFBA) to ...
Measuring the growth rate of filamentous fungi is an essential phenotype assay in fungal biology, enabling the comparison of nutrient-related fitness ...
Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only partially visible on routine MRI, making it difficult ...
Abstract Background: Systematic reviews (SRs) are essential for evidence-based medicine but require extensive time and resources for abstract screenin...
Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only partially visible on routine MRI, making it difficult ...
Computational growth and remodeling (G&R) models have been extentively used to investigate abdominal aortic aneurysm (AAA) progression and to support ...
Natural evolution is high-dimensional; organisms adapt to many pressures at once, across substrates, environments, and genetic backgrounds. Yet most d...
Background: Placental growth and function are imperative for healthy fetal growth; data on placentas can inform research and clinical care. Measuring ...
Large language models (LLMs) are increasingly used by the public to seek health information, yet their reliability in addressing common vaccine myths ...