AI Medical Compendium Topic

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Minority Groups

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Staging study of single-channel sleep EEG signals based on data augmentation.

Frontiers in public health
INTRODUCTION: Accurate sleep staging is an essential basis for sleep quality assessment and plays an important role in sleep quality research. However, the occupancy of different sleep stages is unbalanced throughout the sleep process, which makes th...

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

PLoS computational biology
Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The U...

Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts.

Public health
OBJECTIVES: This study aimed to study the public's sentiments on the current monkeypox outbreaks via an unsupervised machine learning analysis of social media posts.

Generating synthetic personal health data using conditional generative adversarial networks combining with differential privacy.

Journal of biomedical informatics
A large amount of personal health data that is highly valuable to the scientific community is still not accessible or requires a lengthy request process due to privacy concerns and legal restrictions. As a solution, synthetic data has been studied an...

Efficient adversarial debiasing with concept activation vector - Medical image case-studies.

Journal of biomedical informatics
BACKGROUND: A major hurdle for the real time deployment of the AI models is ensuring trustworthiness of these models for the unseen population. More often than not, these complex models are black boxes in which promising results are generated. Howeve...

Conversational AI and equity through assessing GPT-3's communication with diverse social groups on contentious topics.

Scientific reports
Autoregressive language models, which use deep learning to produce human-like texts, have surged in prevalence. Despite advances in these models, concerns arise about their equity across diverse populations. While AI fairness is discussed widely, met...

Machine Learning Strategies for Improved Phenotype Prediction in Underrepresented Populations.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Precision medicine models often perform better for populations of European ancestry due to the over-representation of this group in the genomic datasets and large-scale biobanks from which the models are constructed. As a result, prediction models ma...

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

The British journal of ophthalmology
BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equi...

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

BMC medical informatics and decision making
BACKGROUND: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) in predicting mortality and guiding healthcare decisions. However, AI models may perpetuate or exacerbate existing health disparities due to demographi...

Transfer Learning Prediction of Early Exposures and Genetic Risk Score on Adult Obesity in Two Minority Cohorts.

Prevention science : the official journal of the Society for Prevention Research
Due to ethnic heterogeneity in genetic architecture, genetic risk score (GRS) constructed within the European population generally possesses poor portability in underrepresented non-European populations, but substantial genetic similarity exists acro...