Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Explainable AI for Healthcare: Training Healthcare Workers to Use Artificial Intelligence Techniques to Reduce Medical Negligence in Ghana’s Public Health Act, 2012 (Act 851)
20
Zitationen
7
Autoren
2025
Jahr
Abstract
This analysis examines whether Ghana’s Public Health Act, 2012 (Act 851) imposes adequate legal responsibilities on healthcare facilities concerning personnel training on artificial intelligence (AI) systems and implementation of medical negligence reduction measures. Through an evaluative review of Act 851 provisions on staff qualifications, technology deployment, quality care, safety planning, and risk management benchmarks relative to precedents in Ghana and other countries, critical gaps in binding regulations to incentivize organizational capacity building for mitigating errors, hazards and liabilities from substandard practices were identified. Key recommendations include amending Act 851 to mandate credentialing assurance frameworks, clinical audits, risk assessment models and transparency requirements around reporting quality indicators. Strengthening policy directives will compel internal monitoring, governance, and accountability among healthcare facilities as multilayered negligence prevention strategies. Scientific contributions highlight deficiencies in Ghana’s health legislation regarding contemporary challenges like AI adoption risks and propose legal reforms to modernize regulations to support safer, responsible healthcare delivery nationwide.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.423 Zit.