Pediatrics

Integrating graph and reinforcement learning for vaccination strategies in complex networks.

Pandemics like COVID-19 have a huge impact on human society and the global economy. Vaccines are effective in the fight against these pandemics but often in limited supplies, particularly in the early stages. Thus, it is imperative to distribute such crucial public goods efficiently. Identifying and vaccinating key spreaders (i.e., influential nodes) is an effective approach to break down the viru...

Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.

INTRODUCTION: Stunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, developing new predictive models for LGF using more recent data offers opportunity to enhance model accuracy, interpretability and capture new insights....

Parallel development of object recognition in newborn chicks and deep neural networks.

How do newborns learn to see? We propose that visual systems are space-time fitters, meaning visual development can be understood as a blind fitting p...

Juxtaposition of bone age and sexual maturity rating of the Taiwanese population.

BACKGROUND: Bone age (BA) and sexual maturity rating (SMR) are crucial measures in assessing adolescent growth and development. However, studies speci...

Neural network procedures for the cholera disease system with public health mediations.

Severe gastrointestinal infections and watery diseases like cholera are still a major worldwide medical concern in the developing nations. A mathemati...

Predicting cortical-thalamic functional connectivity using functional near-infrared spectroscopy and graph convolutional networks.

Functional near-infrared spectroscopy (fNIRS) measures cortical hemodynamic changes, yet it cannot collect this information from subcortical structure...

Pediatric Liver Transplant Pathology: An Update and Practical Consideration.

This review provides a summary of the diagnostic approach to pediatric liver transplantation (LT) pathology. It emphasizes the pathologic features of ...

Dynamics of infectious disease mathematical model through unsupervised stochastic neural network paradigm.

The viruses has spread globally and have been impacted lives of people socially and economically, which causes immense suffering throughout the world....

Machine Learning Models as Early Warning Systems for Neonatal Infection.

Neonatal infections pose a significant threat to the health of newborns. Associated morbidity and mortality risks underscore the urgency of prompt dia...

DeepCTG® 2.0: Development and validation of a deep learning model to detect neonatal acidemia from cardiotocography during labor.

Cardiotocography (CTG) is the main tool available to detect neonatal acidemia during delivery. Presently, obstetricians and midwives primarily rely on...

Categorization of Novel Research Ideas Regarding Adolescent Idiopathic Scoliosis Generated by Artificial Intelligence.

Background  The generation of innovative research ideas is crucial to advancing the field of medicine. As physicians face increasingly demanding clini...

Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.

BACKGROUND: Sub-Saharan Africa faces high neonatal and maternal mortality rates due to limited access to skilled healthcare during delivery. This stud...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting with prolonged or late-onset debilitating sequelae o...

AI-assisted patient education: Challenges and solutions in pediatric kidney transplantation.

We are writing in response to the recent publication on the use of artificial intelligence, particularly ChatGPT, in generating educational materials ...

The Developing Human Connectome Project: A fast deep learning-based pipeline for neonatal cortical surface reconstruction.

The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated pro...

Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.

Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can...

Advancing healthcare through mobile collaboration: a survey of intelligent nursing robots research.

Mobile collaborative intelligent nursing robots have gained significant attention in the healthcare sector as an innovative solution to address the ch...

Parental perspectives following the implementation of advanced hybrid closed-loop therapy in children and adolescents with type 1 diabetes and elevated glycaemia.

AIMS: To identify from a parental perspective facilitators and barriers of effective implementation of advanced hybrid closed-loop (AHCL) therapy in c...

Predictive analysis of bullying victimization trajectory in a Chinese early adolescent cohort based on machine learning.

BACKGROUND: The development of bullying victimization among adolescents displays significant individual variability, with general, group-based interve...

Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach.

IntroductionTraumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, with epidural hematoma (EDH) being a severe consequ...