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Cultural Competence

Latest AI and machine learning research in cultural competence for healthcare professionals.

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Showing 1156-1176 of 3,220 articles
AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data

Recent advances in generative models have sparked research on improving model fairness with AI-gen...

Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation

One-class anomaly detection aims to detect objects that do not belong to a predefined normal class...

Visual Cues of Gender and Race are Associated with Stereotyping in Vision-Language Models

Current research on bias in Vision Language Models (VLMs) has important limitations: it is focused...

Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias

Score-based diffusion models have achieved incredible performance in generating realistic images, ...

Biased Heritage: How Datasets Shape Models in Facial Expression Recognition

In recent years, the rapid development of artificial intelligence (AI) systems has raised concerns...

An Analytical Theory of Power Law Spectral Bias in the Learning Dynamics of Diffusion Models

We developed an analytical framework for understanding how the learned distribution evolves during...

Disentangled Knowledge Tracing for Alleviating Cognitive Bias

In the realm of Intelligent Tutoring System (ITS), the accurate assessment of students' knowledge ...

On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process

The double descent phenomenon, which deviates from the traditional bias-variance trade-off theory,...

DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models

Large Multimodal Models (LMMs) have emerged as powerful models capable of understanding various da...

Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo

Bayesian Neural Networks (BNNs) provide a promising framework for modeling predictive uncertainty ...

Image-based food groups and portion prediction by using deep learning.

Chronic diseases such as obesity and hypertension due to malnutrition can be prevented by following ...

Mar 2025 40052549
Transparency and Representation in Clinical Research Utilizing Artificial Intelligence in Oncology: A Scoping Review.

INTRODUCTION: Artificial intelligence (AI) has significant potential to improve health outcomes in o...

Mar 2025 40059400
Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation

Autoregressive (AR) modeling, known for its next-token prediction paradigm, underpins state-of-the...

Learning to Generalize without Bias for Open-Vocabulary Action Recognition

Leveraging the effective visual-text alignment and static generalizability from CLIP, recent video...

UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition

Face recognition (FR) stands as one of the most crucial applications in computer vision. The accur...

The erasure of intensive livestock farming in text-to-image generative AI

Generative AI (e.g., ChatGPT) is increasingly integrated into people's daily lives. While it is kn...

Revealing Treatment Non-Adherence Bias in Clinical Machine Learning Using Large Language Models

Machine learning systems trained on electronic health records (EHRs) increasingly guide treatment ...

Effect of Gender Fair Job Description on Generative AI Images

STEM fields are traditionally male-dominated, with gender biases shaping perceptions of job access...

FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidance

Text-to-image diffusion models often exhibit biases toward specific demographic groups, such as ge...

Defining bias in AI-systems: Biased models are fair models

The debate around bias in AI systems is central to discussions on algorithmic fairness. However, t...

Assessing Large Language Models in Agentic Multilingual National Bias

Large Language Models have garnered significant attention for their capabilities in multilingual n...

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