Pediatrics

The role of the microbiota-gut-brain axis and artificial intelligence in cognitive health of pediatric obstructive sleep apnea: A narrative review.

Pediatric obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder associated with significant neurocognitive and behavioral impairments. Recent studies have highlighted the role of gut microbiota and the microbiota-gut-brain axis (MGBA) in influencing cognitive health in children with OSA. This narrative review aims to summarize current knowledge on the relationship between g...

An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation

Reliable prediction of pediatric obesity can offer a valuable resource to providers, helping them engage in timely preventive interventions before the disease is established. Many efforts have been made to develop ML-based predictive models of obesity, and some studies have reported high predictive performances. However, no commonly used clinical decision support tool based on existing ML models...

Unified HT-CNNs Architecture: Transfer Learning for Segmenting Diverse Brain Tumors in MRI from Gliomas to Pediatric Tumors

Accurate segmentation of brain tumors from 3D multimodal MRI is vital for diagnosis and treatment planning across diverse brain tumors. This paper a...

Access to care improves EHR reliability and clinical risk prediction model performance

Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliabi...

3D Graph Attention Networks for High Fidelity Pediatric Glioma Segmentation

Pediatric brain tumors, particularly gliomas, represent a significant cause of cancer related mortality in children with complex infiltrative growth...

PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language Models

The emergence of Large Language Models (LLMs) in the medical domain has stressed a compelling need for standard datasets to evaluate their question-...

A Self-Learning Multimodal Approach for Fake News Detection

The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading ...

Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation

Accurate and automatic segmentation of brain tumors in multi-parametric magnetic resonance imaging (mpMRI) is essential for quantitative measurement...

Deformation-Aware Segmentation Network Robust to Motion Artifacts for Brain Tissue Segmentation using Disentanglement Learning

Motion artifacts caused by prolonged acquisition time are a significant challenge in Magnetic Resonance Imaging (MRI), hindering accurate tissue seg...

Comparative Performance of Machine Learning Algorithms for Early Genetic Disorder and Subclass Classification

A great deal of effort has been devoted to discovering a particular genetic disorder, but its classification across a broad spectrum of disorder cla...

The Evolution and Future Perspectives of Artificial Intelligence Generated Content

Artificial intelligence generated content (AIGC), a rapidly advancing technology, is transforming content creation across domains, such as text, ima...

HumekaFL: Automated Detection of Neonatal Asphyxia Using Federated Learning

Birth Apshyxia (BA) is a severe condition characterized by insufficient supply of oxygen to a newborn during the delivery. BA is one of the primary ...

TSUBF-Net: Trans-Spatial UNet-like Network with Bi-direction Fusion for Segmentation of Adenoid Hypertrophy in CT

Adenoid hypertrophy stands as a common cause of obstructive sleep apnea-hypopnea syndrome in children. It is characterized by snoring, nasal congest...

Swin fMRI Transformer Predicts Early Neurodevelopmental Outcomes from Neonatal fMRI

Brain development in the first few months of human life is a critical phase characterized by rapid structural growth and functional organization. Ac...

AI-Assisted Application for Pediatric Drug Dosing.

Technology in the medical field is continuously advancing due to its numerous subdomains and the ever-growing medical needs of people. Information sys...

Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes.

Identification of cancer subtypes is a critical step for developing precision medicine. Most cancer subtyping is based on the analysis of RNA sequenci...

Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical condition encountered frequently in daily life, formi...

Deep learning-based design and experimental validation of a medicine-like human antibody library.

Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, th...

RatGene: Gene deletion-addition algorithms using growth to production ratio for growth-coupled production in constraint-based metabolic networks

In computational metabolic design, it is often necessary to modify the original constraint-based metabolic networks to lead to growth-coupled produc...

DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic Models

When simulating metabolite productions with genome-scale constraint-based metabolic models, gene deletion strategies are necessary to achieve growth...