Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence and Cardiology Practice in Nigeria: Are We Ready?
4
Zitationen
6
Autoren
2024
Jahr
Abstract
Cardiovascular diseases are the leading cause of death globally. As cardiovascular risk factors continuously rise to pandemic levels, there is intense pressure worldwide to improve cardiac care in preventive cardiology, cardio-diagnostics, therapeutics, and interventional cardiology. Artificial intelligence (AI), an advanced branch of computer science has ushered in the fourth industrial revolution with myriad opportunities in healthcare including cardiology. The developed world has embraced the technology, and the pressure not to be left behind is intense for both policymakers and practicing physicians/cardiologists in low to middle-income countries (LMICs) like Nigeria. This is especially daunting for LMICs who are already plagued with a high burden of infectious disease, unemployment, physician burnt, brain drain, and a developing cardiac practice. Should the focus of cardiovascular care be on men or machines? Is the technology sustainable in a low-resource setting? What lessons did we learn from the COVID-19 pandemic? We attempt to zero in on the dilemmas of AI in the Nigerian setting including AI acceptance, the bottlenecks of cardiology practice in Nigeria, the role of AI, and the type of AI that may be adapted to strengthen cardiovascular care of Nigerians.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.250 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.109 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.482 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 · 5.434 Zit.