AIMC Topic: Healthcare Disparities

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Mavacamten in hypertrophic obstructive cardiomyopathy: Prospects for AI integration and mitigating healthcare disparities.

Current problems in cardiology
Hypertrophic obstructive cardiomyopathy (HOCM) is an autosomal dominant condition that still remains significantly under-diagnosed worldwide. Early detection through clinical evaluation, imaging, and familial history is crucial to prevent severe comp...

Free access via computational cloud to deep learning-based EEG assessment in neonatal hypoxic-ischemic encephalopathy: revolutionary opportunities to overcome health disparities.

Pediatric research
In this issue of Pediatric Research, Kota et al. evaluate a novel monitoring visual trend using deep-learning - Brain State of the Newborn (BSN)- based EEG as a bedside marker for severity of the encephalopathy in 46 neonates with hypoxic-ischemic en...

Use of artificial intelligence to address health disparities in low- and middle-income countries: a thematic analysis of ethical issues.

Public health
OBJECTIVES: Artificial intelligence (AI) is reshaping health and medicine, especially through its potential to address health disparities in low- and middle-income countries (LMICs). However, there are several issues associated with the use of AI tha...

Bridging Health Disparities in the Data-Driven World of Artificial Intelligence: A Narrative Review.

Journal of racial and ethnic health disparities
BACKGROUND: Artificial intelligence (AI) holds exciting potential to revolutionize healthcare delivery in the United States. However, there are concerns about its potential to perpetuate disparities among historically marginalized populations.

Machine learning evaluation of inequities and disparities associated with nurse sensitive indicator safety events.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To use machine learning to examine health equity and clinical outcomes in patients who experienced a nurse sensitive indicator (NSI) event, defined as a fall, a hospital-acquired pressure injury (HAPI) or a hospital-acquired infection (HAI).

Challenges of artificial intelligence in medicine and dermatology.

Clinics in dermatology
Artificial intelligence (AI) in medicine and dermatology brings additional challenges related to bias, transparency, ethics, security, and inequality. Bias in AI algorithms can arise from biased training data or decision-making processes, leading to ...

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...