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Work Force

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

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TRIX- Trading Adversarial Fairness via Mixed Adversarial Training

Adversarial Training (AT) is a widely adopted defense against adversarial examples. However, exist...

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy

We investigate Machine-Learned Force Fields (MLFFs) trained on approximate Density Functional Theo...

Prompt-Free Conditional Diffusion for Multi-object Image Augmentation

Diffusion models has underpinned much recent advances of dataset augmentation in various computer ...

Conditional Graph Neural Network for Predicting Soft Tissue Deformation and Forces

Soft tissue simulation in virtual environments is becoming increasingly important for medical appl...

CP-Dilatation: A Copy-and-Paste Augmentation Method for Preserving the Boundary Context Information of Histopathology Images

Medical AI diagnosis including histopathology segmentation has derived benefits from the recent de...

SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights

With the rise and development of computer vision and LLMs, intelligence is everywhere, especially ...

Inverse Synthetic Aperture Fourier Ptychography

Fourier ptychography (FP) is a powerful light-based synthetic aperture imaging technique that allo...

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs

The foundational capabilities of large language models (LLMs) are deeply influenced by the quality...

Multimodal Mathematical Reasoning with Diverse Solving Perspective

Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capa...

Beyond Overcorrection: Evaluating Diversity in T2I Models with DivBench

Current diversification strategies for text-to-image (T2I) models often ignore contextual appropri...

Beyond Overcorrection: Evaluating Diversity in T2I Models with DIVBENCH

Current diversification strategies for text-to-image (T2I) models often ignore contextual appropri...

A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs

Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is in...

Cells Keep Diverse Company in Diseased Tissues.

Emerging spatial profiling technologies have revolutionized our understanding of how tissue architec...

Jul 2025 40378285
MedDiff-FT: Data-Efficient Diffusion Model Fine-tuning with Structural Guidance for Controllable Medical Image Synthesis

Recent advancements in deep learning for medical image segmentation are often limited by the scarc...

Impact of Noisy Supervision in Foundation Model Learning.

Foundation models are usually pre-trained on large-scale datasets and then adapted to different down...

Jul 2025 40117144
SigPhi-Med: A lightweight vision-language assistant for biomedicine.

BACKGROUND: Recent advancements in general multimodal large language models (MLLMs) have led to subs...

Jul 2025 40456503
Current and future directions for the use of handheld fundus cameras in telehealth.

INTRODUCTION: A shortage of trained retinal specialists has created a growing need for a telehealth ...

Jul 2025 40410947
Beyond Accuracy: Evaluating certainty of AI models for brain tumour detection.

Brain tumors pose a severe health risk, often leading to fatal outcomes if not detected early. While...

Jul 2025 40424764
FedELR: When federated learning meets learning with noisy labels.

Existing research on federated learning (FL) usually assumes that training labels are of high qualit...

Jul 2025 40081270
Adoption of artificial intelligence in healthcare: survey of health system priorities, successes, and challenges.

IMPORTANCE: The US healthcare system faces significant challenges, including clinician burnout, oper...

Jul 2025 40323320
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