Using machine learning systems to predict occupational hearing loss for mineworkers in South Africa: A case study of ethical challenges to research in preventive audiology in the mining industry

Machine learning models: Predictive tools for occupational noise-induced hearing loss in the South African mining industry

Occupational noise induced hearing loss in the mining sector in South Africa: Perspectives from occupational health practitioners on how mineworkers are trained

The aim of this study was to explore the perspectives of occupational health practitioners (OHPs) re

Diverse experts’ perspectives on ethical issues of using machine learning to predict HIV/AIDS risk in sub-Saharan Africa: a modified Delphi study

Objective To better understand diverse experts’ views about the ethical implic

Using Machine Learning to Predict Resilience Among Nurses in a South African Setting

Nursing is a stressful profession. Stress can affect the mental health of nurses. A positive respons

Occupational Hearing loss in Africa: An interdisciplinary view of the current status

Noise-induced hearing loss is 100% preventable if the collaborative stakeholders in the prevention p

Mapping legislative and regulatory frameworks for preventive audiology in Africa: progress and challenges

Background Hearing loss represents a significant and growing public health cha