ArticleAnnals of global health2021
Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.
Article in Annals of global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 18 citations in OpenAlex.
- A multimodal deep learning framework for precise silicosis detection on radiographic images.Scientific reports · 2026Article
- The Case for Local AI Development: Lessons From Computer‑Aided Detection of Tuberculosis and Silicosis in Southern Africa's Ex‑Miners.Annals of global health · 2026Article
- Translating and Adapting Research Bioethical Principles to the African Socio-Cultural Contexts: An Integrative Review.African journal of bioethics · 2026Article
- Cytokine Profiles as Predictive Biomarkers of Disease Severity and Progression in Engineered Stone Silicosis: A Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2025Article
- Ethical and social considerations of applying artificial intelligence in healthcare-a two-pronged scoping review.BMC medical ethics · 2025Article
- Determining Thresholds for Computer-Aided Detection for Silicosis-An Analytic Approach.American journal of industrial medicine · 2025Article
- Unmet Occupational Health Needs of Malawian Ex-Miners from the South African Gold Mines.Annals of global health · 2025Article
- Bio-ethical considerations in the application of artificial intelligence in spinal surgery.Brain & spine · 2025Article
- Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers.Bioengineering & translational medicine · 2024Article
- A Systematic Review of Artificial Intelligence Applications in the Management of Lung Disorders.Cureus · 2024Review
- Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions --A Bibliometric Analysis from 2009 to 2023.International journal of chronic obstructive pulmonary disease · 2024Article
- Accuracy of Computer-Aided Detection of Occupational Lung Disease: Silicosis and Pulmonary Tuberculosis in Ex-Miners from the South African Gold Mines.International journal of environmental research and public health · 2022Article
- Reforming the workers' compensation process for occupational lung disease among miners in South Africa: an efficiency study of claims assessment.International archives of occupational and environmental health · 2022Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although Artificial Intelligence (AI) is being increasingly applied, considerable distrust about introducing "disruptive" technologies persists. Intrinsic and contextual factors influencing where and how such innovations are introduced therefore require careful scrutiny to ensure that health equity is promoted. To illustrate one such critical approach, we describe and appraise an AI application - the development of computer assisted diagnosis (CAD) to support more efficient adjudication of compensation claims from former gold miners with occupational lung disease in Southern Africa. In doing so, we apply a bio-ethical lens that considers the principles of beneficence, non-maleficence, autonomy and justice and add explicability as a core principle. We draw on the AI literature, our research on CAD validation and process efficiency, as well as apprehensions of users and stakeholders. Issues of concern included AI accuracy, biased training of AI systems, data privacy, impact on human skill development, transparency and accountability in AI use, as well as intellectual property ownership. We discuss ways in which each of these potential obstacles to successful use of CAD could be mitigated. We conclude that efforts to overcoming technical challenges in applying AI must be accompanied from the onset by attention to ensuring its ethical use.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.