Cultural Competence

Enhancing Patient-Physician Communication: Simulating African American Vernacular English in Medical Diagnostics with Large Language Models.

UNLABELLED: Effective communication is crucial in reducing health disparities. However, linguistic differences, such as African American Vernacular English (AAVE), can lead to communication gaps between patients and physicians, negatively affecting care and outcomes. This study examines whether large language models (LLMs), specifically GPT-4 and Llama 3.3, can replicate AAVE in simulated clinical...

Equitable machine learning counteracts ancestral bias in precision medicine.

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease. Therapeutics and outcomes remain hidden because we lack insights that could be gained from analyzing ancestrally diverse genomic data. To address this significant gap, we present PhyloFrame, a machine learning method for equitable genomic precision m...

Overconfident, but angry at least. AI-Based investigation of facial emotional expressions and self-assessment bias in human adults.

Metacognition and facial emotional expressions both play a major role in human social interactions [1, 2] as inner narrative and primary communication...

FedBM: Stealing knowledge from pre-trained language models for heterogeneous federated learning.

Federated learning (FL) has shown great potential in medical image computing since it provides a decentralized learning paradigm that allows multiple ...

Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying appearances across images, including differences ...

Cognitive biases in forensic psychiatry: A scoping review.

Forensic psychiatry plays a critical role in legal contexts but is highly susceptible to cognitive biases that can undermine the accuracy and objectiv...

Quantitative analysis and evaluation of winter and summer landscape colors in the Yangzhou ancient Canal utilizing deep learning.

Color is an important index for human visual evaluation of landscape, and it is also a key factor affecting people's recognition and experience of her...

The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview Part 2: The Promise and Perils, and the International Dental Federation Communique.

In the final part of this two part article on artificial intelligence (AI) in dentistry we review its transformative role, focusing on AI in dental ed...

Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence.

With the development of digital health, enhancing decision-making effectiveness has become a critical task. This study proposes an improved Artificial...

Replica tree-based federated learning using limited data.

Learning from limited data has been extensively studied in machine learning, considering that deep neural networks achieve optimal performance when tr...

Perspectives of Black, Latinx, Indigenous, and Asian Communities on Health Data Use and AI: Cross-Sectional Survey Study.

Despite excitement around artificial intelligence (AI)-based tools in health care, there is work to be done before they can be equitably deployed. The...

Integrating enterprise risk management to address AI-related risks in healthcare: Strategies for effective risk mitigation and implementation.

The incorporation of artificial intelligence (AI) in health care offers revolutionary enhancements in patient diagnostics, clinical processes, and ove...

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.

Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and f...

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 functional relevance and regulatory mechanisms. CircRNA su...

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

The rapid integration of deep learning-powered artificial intelligence systems in diverse applications such as healthcare, credit assessment, employme...

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 from development to application. The complexity and i...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk i...

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 power that comes with great responsibility. Their ...

Biomechanical Risk Classification in Repetitive Lifting Using Multi-Sensor Electromyography Data, Revised National Institute for Occupational Safety and Health Lifting Equation, and Deep Learning.

Repetitive lifting tasks in occupational settings often result in shoulder injuries, impacting both health and productivity. Accurately assessing the ...

Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.

This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using on...