Pediatrics

UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis

Functional ultrasound (fUS) is a neuroimaging technique known for its high spatiotemporal resolution, enabling non-invasive observation of brain activity through neurovascular coupling. Despite its potential in clinical applications such as neonatal monitoring and intraoperative guidance, the development of fUS faces challenges related to data scarcity and limitations in generating realistic fUS...

Intelligent Histology for Tumor Neurosurgery

The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standard-of-care intraoperative pathology workflow is based on light microscopy and H\&E histology, which is slow, resource-intensive, and lacks real-time digital imaging capabilities. Here, we present an emerging and innovative method for intraoperative h...

Designing for Community Care: Reimagining Support for Equity & Well-being in Academia

Academic well-being is deeply influenced by peer-support networks, yet they remain informal, inequitable, and unsustainable, often relying on person...

Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound

Fetal abdominal malformations are serious congenital anomalies that require accurate diagnosis to guide pregnancy management and reduce mortality. A...

CHRONIC CRITICAL ILLNESS IN BONE TRAUMA PATIENTS: AN AI-BASED APPROACH FOR INTENSIVE CARE UNIT HEALTHCARE PROVIDERS.

Background: Chronic critical illness (CCI) is a serious condition characterized by a prolonged course of illness, resulting in elevated morbidity and ...

Predictive Modeling of Human Skin Deformation and Growth During Tissue Expansion in Postmastectomy Breast Reconstruction.

Breast reconstruction using tissue expanders is the primary treatment option following mastectomy. Although skin growth in response to chronic supra-p...

Building efficiency: How the national AI innovation pilot zones enhance green energy utilization? Evidence from China.

Improving energy efficiency is a pivotal strategy for achieving energy conservation, emission reduction, and green development goals, while also servi...

Comparative Analysis of Information Quality in Pediatric Otorhinolaryngology: Clinicians, Residents, and Large Language Models.

OBJECTIVE: Pediatric otorhinolaryngology (ORL) addresses complex conditions in children, requiring a tailored approach for patients and families. With...

Circapproved: Digital Pattern Recognition via Artificial Neural Network for the Identification of Normal Penis Parameters for Circumcision Eligibility Using Mobile App.

BACKGROUND: Circumcision is a prevalent surgical procedure performed for medical, cultural, and religious reasons, requiring a thorough assessment of ...

Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy.

PURPOSES: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatr...

Artificial intelligence in pediatric otolaryngology: A state-of-the-art review of opportunities and pitfalls.

BACKGROUND: Artificial Intelligence (AI) and machine learning (ML) have transformative potential in enhancing diagnostics, treatment planning, and pat...

Auto-TA: Towards Scalable Automated Thematic Analysis (TA) via Multi-Agent Large Language Models with Reinforcement Learning

Congenital heart disease (CHD) presents complex, lifelong challenges often underrepresented in traditional clinical metrics. While unstructured narr...

Transition Matching: Scalable and Flexible Generative Modeling

Diffusion and flow matching models have significantly advanced media generation, yet their design space is well-explored, somewhat limiting further ...

Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound

Congenital uterine anomalies (CUAs) can lead to infertility, miscarriage, preterm birth, and an increased risk of pregnancy complications. Compared ...

Predicting treatment outcome in congenital adrenal hyperplasia using urine steroidomics and machine learning.

OBJECTIVE: Treatment monitoring of individuals with congenital adrenal hyperplasia (CAH) remains unsatisfactory. Comprehensive 24 h urine steroid prof...

BPD-Neo: An MRI Dataset for Lung-Trachea Segmentation with Clinical Data for Neonatal Bronchopulmonary Dysplasia

Bronchopulmonary dysplasia (BPD) is a common complication among preterm neonates, with portable X-ray imaging serving as the standard diagnostic mod...

Point Cloud Compression and Objective Quality Assessment: A Survey

The rapid growth of 3D point cloud data, driven by applications in autonomous driving, robotics, and immersive environments, has led to criticals de...

Predicting the morphology of cobalt, copper, and ruthenium on TaN for interconnect metal deposition.

Downscaling of metal interconnects has become a bottleneck in the back-end-of-line processing of CMOS semiconductor devices. The conductivity of the c...

High Resolution Isotropic 3D Cine imaging with Automated Segmentation using Concatenated 2D Real-time Imaging and Deep Learning

Background: Conventional cardiovascular magnetic resonance (CMR) in paediatric and congenital heart disease uses 2D, breath-hold, balanced steady st...

Fetal Sleep: A Cross-Species Review of Physiology, Measurement, and Classification

Fetal sleep is a relatively underexplored yet vital aspect of prenatal neurodevelopment. Understanding fetal sleep patterns could provide insights i...