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Cultural Competence

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

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Bias Amplification to Facilitate the Systematic Evaluation of Bias Mitigation Methods.

The future of artificial intelligence (AI) safety is expected to include bias mitigation methods fro...

UnBias: Unveiling Bias Implications in Deep Learning Models for Healthcare Applications.

The rapid integration of deep learning-powered artificial intelligence systems in diverse applicatio...

CellCircLoc: Deep Neural Network for Predicting and Explaining Cell Line-Specific CircRNA Subcellular Localization.

The subcellular localization of circular RNAs (circRNAs) is crucial for understanding their function...

Is more data always better? On alternative policies to mitigate bias in Artificial Intelligence health systems.

The development and implementation of Artificial Intelligence (AI) health systems represent a great ...

The Data Artifacts Glossary: a community-based repository for bias on health datasets.

BACKGROUND: The deployment of Artificial Intelligence (AI) in healthcare has the potential to transf...

Me vs. the machine? Subjective evaluations of human- and AI-generated advice.

Artificial intelligence ("AI") has the potential to vastly improve human decision-making. In line wi...

COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation.

Current research on next point-of-interest (POI) recommendation focuses on capturing users' behavior...

Addressing grading bias in rock climbing: machine and deep learning approaches.

The determination rock climbing route difficulty is notoriously subjective. While there is no offici...

Ethical and security challenges in AI for forensic genetics: From bias to adversarial attacks.

Forensic scientists play a crucial role in assigning probabilities to evidence based on competing hy...

Combining various training and adaptation algorithms for ensemble few-shot classification.

To mitigate the shortage of labeled data, Few-Shot Classification (FSC) methods train deep neural ne...

AI Can Be a Powerful Social Innovation for Public Health if Community Engagement Is at the Core.

There is a critical need for community engagement in the process of adopting artificial intelligence...

On spectral bias reduction of multi-scale neural networks for regression problems.

In this paper, we derive diffusion equation models in the spectral domain to study the evolution of ...

Enhancing Domain Diversity of Transfer Learning-Based SSVEP-BCIs by the Reconstruction of Channel Correlation.

OBJECTIVE: The application of transfer learning, specifically pre-training and fine-tuning, in stead...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-trau...

Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI.

A growing number of covariate modeling methods have been proposed in the field of popPK modeling, bu...

Responsible Design, Integration, and Use of Generative AI in Mental Health.

Generative artificial intelligence (GenAI) shows potential for personalized care, psychoeducation, a...

Reducing bias in source-free unsupervised domain adaptation for regression.

Due to data privacy and storage concerns, Source-Free Unsupervised Domain Adaptation (SFUDA) focuses...

CPJN: News recommendation with a content and popularity joint network.

Users may click on a news because they are interested in its content or because the news contains im...

Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach.

BACKGROUND: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) i...

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