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Cultural Competence

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

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Showing 274-294 of 3,657 articles
Issues and Limitations on the Road to Fair and Inclusive AI Solutions for Biomedical Challenges.

OBJECTIVE: In this paper, we explore the correlation between performance reporting and the developme...

Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.

Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with research...

Why robot embodiment matters: questions of disability, race and intersectionality in the design of social robots.

A growing minority of those with disabilities are people of color (POC), with, for example, autism d...

Prompt-Driven Latent Domain Generalization for Medical Image Classification.

Deep learning models for medical image analysis easily suffer from distribution shifts caused by dat...

Boosting Your Context by Dual Similarity Checkup for In-Context Learning Medical Image Segmentation.

The recent advent of in-context learning (ICL) capabilities in large pre-trained models has yielded ...

Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images.

OBJECTIVE: This study aims to assess and compare two state-of-the-art deep learning approaches for s...

A computational deep learning investigation of animacy perception in the human brain.

The functional organization of the human object vision pathway distinguishes between animate and ina...

Whither bias goes, I will go: An integrative, systematic review of algorithmic bias mitigation.

Machine learning (ML) models are increasingly used for personnel assessment and selection (e.g., res...

Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation.

Unsupervised domain adaptation (UDA) has shown impressive performance by improving the generalizabil...

Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.

Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge...

Utilising causal inference methods to estimate effects and strategise interventions in observational health data.

Randomised controlled trials (RCTs) are the gold standard for evaluating health interventions but of...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support ep...

Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review.

This systematic review aimed to evaluate the application of artificial intelligence (AI) in the iden...

Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BACKGROUND: Accurate prediction of copy number variations (CNVs) from targeted capture next-generati...

Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research.

Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense prom...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after ...

Biosecurity measures reducing spp. and hepatitis E virus prevalence in pig farms-a systematic review and meta-analysis.

spp. and hepatitis E virus (HEV) are significant foodborne zoonotic pathogens that impact the healt...

Enhancing consistency and mitigating bias: A data replay approach for incremental learning.

Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, a...

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