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Cultural Competence

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

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NeuroLIP: Interpretable and Fair Cross-Modal Alignment of fMRI and Phenotypic Text

Integrating functional magnetic resonance imaging (fMRI) connectivity data with phenotypic textual...

Sacred or Secular? Religious Bias in AI-Generated Financial Advice

This study examines religious biases in AI-generated financial advice, focusing on ChatGPT's respo...

Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability

Diffusion models have demonstrated impressive capabilities in synthesizing diverse content. Howeve...

Dynamics of Algorithmic Content Amplification on TikTok

Intelligent algorithms increasingly shape the content we encounter and engage with online. TikTok'...

Reflections on Diversity: A Real-time Virtual Mirror for Inclusive 3D Face Transformations

Real-time 3D face manipulation has significant applications in virtual reality, social media and h...

Beyond Relevance: An Adaptive Exploration-Based Framework for Personalized Recommendations

Recommender systems must balance personalization, diversity, and robustness to cold-start scenario...

HingeRLC-GAN: Combating Mode Collapse with Hinge Loss and RLC Regularization

Recent advances in Generative Adversarial Networks (GANs) have demonstrated their capability for p...

LakotaBERT: A Transformer-based Model for Low Resource Lakota Language

Lakota, a critically endangered language of the Sioux people in North America, faces significant c...

MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection

Mathematical error detection in educational settings presents a significant challenge for Multimod...

Bayesian generative models can flag performance loss, bias, and out-of-distribution image content

Generative models are popular for medical imaging tasks such as anomaly detection, feature extract...

Does a Rising Tide Lift All Boats? Bias Mitigation for AI-based CMR Segmentation

Artificial intelligence (AI) is increasingly being used for medical imaging tasks. However, there ...

When Tom Eats Kimchi: Evaluating Cultural Bias of Multimodal Large Language Models in Cultural Mixture Contexts

In a highly globalized world, it is important for multi-modal large language models (MLLMs) to rec...

Chain of Functions: A Programmatic Pipeline for Fine-Grained Chart Reasoning Data

Visual reasoning is crucial for multimodal large language models (MLLMs) to address complex chart ...

Probabilistic Prompt Distribution Learning for Animal Pose Estimation

Multi-species animal pose estimation has emerged as a challenging yet critical task, hindered by s...

Bias Evaluation and Mitigation in Retrieval-Augmented Medical Question-Answering Systems

Medical Question Answering systems based on Retrieval Augmented Generation is promising for clinic...

Exploring Disparity-Accuracy Trade-offs in Face Recognition Systems: The Role of Datasets, Architectures, and Loss Functions

Automated Face Recognition Systems (FRSs), developed using deep learning models, are deployed worl...

Boosting Semi-Supervised Medical Image Segmentation via Masked Image Consistency and Discrepancy Learning

Semi-supervised learning is of great significance in medical image segmentation by exploiting unla...

Identifying and Mitigating Position Bias of Multi-image Vision-Language Models

The evolution of Large Vision-Language Models (LVLMs) has progressed from single to multi-image re...

Unlock Pose Diversity: Accurate and Efficient Implicit Keypoint-based Spatiotemporal Diffusion for Audio-driven Talking Portrait

Audio-driven single-image talking portrait generation plays a crucial role in virtual reality, dig...

DivCon-NeRF: Generating Augmented Rays with Diversity and Consistency for Few-shot View Synthesis

Neural Radiance Field (NeRF) has shown remarkable performance in novel view synthesis but requires...

Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model

Image generative models, particularly diffusion-based models, have surged in popularity due to the...

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