Pediatrics

Can Local Vision-Language Models improve Activity Recognition over Vision Transformers? -- Case Study on Newborn Resuscitation

Accurate documentation of newborn resuscitation is essential for quality improvement and adherence to clinical guidelines, yet remains underutilized in practice. Previous work using 3D-CNNs and Vision Transformers (ViT) has shown promising results in detecting key activities from newborn resuscitation videos, but also highlighted the challenges in recognizing such fine-grained activities. This wor...

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting our ability to diagnose failures, understand dataset shift, or intervene in a principled manner. We introduce Med-SegLens, a model-diffing framework that decomposes segmentation model activations into interpretable latent features using sparse autoencoders trained on SegFormer and U-Net. Through cr...

Design, Development, and Use of Maya Robot as an Assistant for the Therapy/Education of Children with Cancer: a Pilot Study

This study centers around the design and implementation of the Maya Robot, a portable elephant-shaped social robot, intended to engage with children u...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression ...

When attention falters: brain, breathing, and behavioral signals of lapses in interoceptive attention

Mind-body practices like meditation and yoga, which are widely used to support mental health, involve paying attention to internal bodily sensations l...

Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields

Modeling the time-varying 3D appearance of plants during their growth poses unique challenges: unlike many dynamic scenes, plants generate new geometr...

Deep Learning-Based Automated Echocardiographic Measurements in Pediatric and Congenital Heart Disease

Background: Echocardiography (echo) is a cornerstone of pediatric cardiology, yet access to expert interpreters is limited worldwide, particularly in ...

Image Quality Evaluation of Neonatal Brain MRI Using a Deep Learning Reconstruction Algorithm: A Quantitative and Multireader Study Using Variable Denoising Levels at 3 Tesla

Purpose: Neonatal imaging is particularly challenging because newborns have a high likelihood of head motion, which can degrade image quality and comp...

Generative Regression for Left Ventricular Ejection Fraction Estimation from Echocardiography Video

Estimating Left Ventricular Ejection Fraction (LVEF) from echocardiograms constitutes an ill-posed inverse problem. Inherent noise, artifacts, and lim...

Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields

Modeling the time-varying 3D appearance of plants during their growth poses unique challenges: unlike many dynamic scenes, plants generate new geometr...

WristMIR: Coarse-to-Fine Region-Aware Retrieval of Pediatric Wrist Radiographs with Radiology Report-Driven Learning

Retrieving wrist radiographs with analogous fracture patterns is challenging because clinically important cues are subtle, highly localized and often ...

Estimating Gait Kinematics from Muscle Activity Using Deep Learning in Typically Developing Children

Instrumented gait assessment in pediatric populations is often constrained by the complexity and lack of portability of traditional motion capture sys...

Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography

Fetal echocardiography is essential for detecting congenital heart disease (CHD), facilitating pregnancy management, optimized delivery planning, and ...

Predictive Modeling of COVID-19 Variant Peak Prevalence and Duration Using GISAID Data Across 15 Countries

BackgroundRapid emergence and replacement of SARS-CoV-2 variants underscore the need for early and reliable indicators of variant dominance to guide t...

A Mixed Reality System for Robust Manikin Localization in Childbirth Training

Opportunities for medical students to gain practical experience in vaginal births are increasingly constrained by shortened clinical rotations, patien...

Neonatal auditory input affects vocal development in harbour seals.

Vocal individuality has important biological functions in mammals: at crucial stages of development, it ensures feeding and is a prerequisite for audi...

Opportunities and mechanisms for learning through social interactions: lessons from marmosets.

Social interactions are crucial for learning not only in humans but also in non-human animals. To date, comparative studies have typically focused on ...

Artificial Intelligence-Driven Adaptation of Pediatric Traumatic Brain Injury Case Descriptions for Family Communication.

OBJECTIVE: We examined whether GPT-4o, a widely used large language model (LLM), could produce age- and education-appropriate versions of complex pedi...

Long-term Cardiac Autonomic Effects of Prenatal Steroid Exposure: A Machine Learning Approach Integrating Heart Rate Variability and ECG Foundation Models

Background: Prenatal glucocorticoid administration is standard care for threatened preterm birth, but long-term cardiac autonomic effects remain incom...

Development and internal validation of risk scores to predict survival in the pediatric population following in-hospital cardiac arrest.

Introduction In-hospital cardiac arrest (IHCA) in the pediatric population is associated with poor survival and neurological outcomes. We aimed to dev...