Pediatrics

ADHD/ADD

Latest AI and machine learning research in adhd/add for healthcare professionals.

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Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models

Concept unlearning aims to erase a target concept from a pretrained text-to-image diffusion model wi...

Predicting first-onset depression in adolescents: Do general population models generalize to youth with ADHD?

Background: Most studies seeking to identify youth at increased risk for depression have developed p...

Additive baselines furnish no evidence for epistasis learning by MULTI-evolve

Recent work from Tran et al. (Science, 2026) introduced MULTI-evolve, a framework for protein engine...

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity

Several brain foundation models (FM) have recently been proposed to predict brain disorders by model...

Evaluating Large Language Models for Transparent Quality-of-Care Measurement in Children with ADHD

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder...

ADD for Multi-Bit Image Watermarking

As generative models enable rapid creation of high-fidelity images, societal concerns about misinfor...

D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose neu...

DuSCN-FusionNet: An Interpretable Dual-Channel Structural Covariance Fusion Framework for ADHD Classification Using Structural MRI

Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental condition; ...

CardioDiT: Latent Diffusion Transformers for 4D Cardiac MRI Synthesis

Latent diffusion models (LDMs) have recently achieved strong performance in 3D medical image synthes...

Counting Circuits: Mechanistic Interpretability of Visual Reasoning in Large Vision-Language Models

Counting serves as a simple but powerful test of a Large Vision-Language Model's (LVLM's) reasoning;...

DriveTok: 3D Driving Scene Tokenization for Unified Multi-View Reconstruction and Understanding

With the growing adoption of vision-language-action models and world models in autonomous driving sy...

Motion-Adaptive Temporal Attention for Lightweight Video Generation with Stable Diffusion

We present a motion-adaptive temporal attention mechanism for parameter-efficient video generation b...

The Unreasonable Effectiveness of Text Embedding Interpolation for Continuous Image Steering

We present a training-free framework for continuous and controllable image editing at test time for ...

Detection of Autonomous Shuttles in Urban Traffic Images Using Adaptive Residual Context

The progressive automation of transport promises to enhance safety and sustainability through shared...

Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification

Brain imaging classification is commonly approached from two perspectives: modeling the full image v...

Locality-Attending Vision Transformer

Vision transformers have demonstrated remarkable success in classification by leveraging global self...

Decomposing response inhibition: a POMDP model

Inhibition is a core cognitive control function whose competence is distributed across the populatio...

PartRAG: Retrieval-Augmented Part-Level 3D Generation and Editing

Single-image 3D generation with part-level structure remains challenging: learned priors struggle to...

Automated Histopathology Report Generation via Pyramidal Feature Extraction and the UNI Foundation Model

Generating diagnostic text from histopathology whole slide images (WSIs) is challenging due to the g...

Focused ultrasound neuromodulation of mediodorsal thalamus disrupts decision flexibility during reward learning

When learning to find the most beneficial course of action, the prefrontal cortex guides decisions b...

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