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Work Force

Latest AI and machine learning research in work force for healthcare professionals.

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Lung Nodule Image Synthesis Driven by Two-Stage Generative Adversarial Networks

The limited sample size and insufficient diversity of lung nodule CT datasets severely restrict the ...

MoE-ACT: Improving Surgical Imitation Learning Policies through Supervised Mixture-of-Experts

Imitation learning has achieved remarkable success in robotic manipulation, yet its application to s...

From Cold Start to Active Learning: Embedding-Based Scan Selection for Medical Image Segmentation

Accurate segmentation annotations are critical for disease monitoring, yet manual labeling remains a...

Entropy-Guided Agreement-Diversity: A Semi-Supervised Active Learning Framework for Fetal Head Segmentation in Ultrasound

Fetal ultrasound (US) data is often limited due to privacy and regulatory restrictions, posing chall...

SCHIGAND: A Synthetic Facial Generation Mode Pipeline

The growing demand for diverse and high-quality facial datasets for training and testing biometric s...

StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors

Annotating medical data for training AI models is often costly and limited due to the shortage of sp...

AI-generated data contamination erodes pathological variability and diagnostic reliability

Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content...

RSOD: Reliability-Guided Sonar Image Object Detection with Extremely Limited Labels

Object detection in sonar images is a key technology in underwater detection systems. Compared to na...

Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data

Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whe...

AI-generated data contamination erodes pathological variability and diagnostic reliability

Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content...

Organ-Aware Attention Improves CT Triage and Classification

There is an urgent need for triage and classification of high-volume medical imaging modalities such...

Generating Structurally Diverse Therapeutic Peptides with GFlowNet

Reinforcement learning approaches for therapeutic peptide generation suffer from mode collapse, conv...

A Two-Stage Globally-Diverse Adversarial Attack for Vision-Language Pre-training Models

Vision-language pre-training (VLP) models are vulnerable to adversarial examples, particularly in bl...

Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Versatile Image Generation

Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning large-scale generativ...

Generation of Chest CT pulmonary Nodule Images by Latent Diffusion Models using the LIDC-IDRI Dataset

Recently, computer-aided diagnosis systems have been developed to support diagnosis, but their perfo...

Onco-Seg: Adapting Promptable Concept Segmentation for Multi-Modal Medical Imaging

Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radi...

MorphoLearn: A morphology-driven workflow to decipher 3D electron microscopy segmentation in diatoms

Three-dimensional electron microscopy (3D EM) enables the quantitative analysis of cellular ultrastr...

POWDR: Pathology-preserving Outpainting with Wavelet Diffusion for 3D MRI

Medical imaging datasets often suffer from class imbalance and limited availability of pathology-ric...

HS-GC-IMS couples with convolutional neural network for Burkholderia gladioli pv. Cocovenenans detection in Auricularia Auricula.

The shortage in early detection methods for the pathogen Burkholderia gladioli pv. cocovenenans (BGC...

Sep 2025 40349514
Subject-Consistent and Pose-Diverse Text-to-Image Generation

Subject-consistent generation (SCG)-aiming to maintain a consistent subject identity across divers...

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