Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust

Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust

AI has the potential to disrupt and transform the way we deliver care globally. It is reputed to be able to improve the accuracy of diagnoses and treatments, and make the provision of services more efficient and effective. In surgery, AI systems could lead to more accurate diagnoses of health proble...

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Bibliografiske detaljer
Hovedforfatter:	Kerasidou, A
Format:	Journal article
Sprog:	English
Udgivet:	Elsevier 2021

Lignende værker

Ethics of artificial intelligence in global health: Explainability, algorithmic bias and trust
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Artificial intelligence and the ongoing need for empathy, compassion and trust in healthcare
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Udgivet: (2020)

The role of trust in global health research collaborations
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Healthcare Trust Evolution with Explainable Artificial Intelligence: Bibliometric Analysis
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Applied artificial intelligence for global child health: Addressing biases and barriers
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Applied artificial intelligence for global child health: Addressing biases and barriers.
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Udgivet: (2024-08-01)

Austerity, health and ethics
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Udgivet: (2019)

Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care
af: Dlugatch, R, et al.
Udgivet: (2023)

Explainable Artificial Intelligence Methods to Enhance Transparency and Trust in Digital Deliberation Settings
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Udgivet: (2024-07-01)

Bias in artificial intelligence algorithms and recommendations for mitigation.
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Udgivet: (2023-06-01)

Bias in artificial intelligence algorithms and recommendations for mitigation
af: Lama H. Nazer, et al.
Udgivet: (2023-06-01)

Acceptance, initial trust formation, and human biases in artificial intelligence: Focus on clinicians
af: Avishek Choudhury, et al.
Udgivet: (2022-08-01)

Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care
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Udgivet: (2023-06-01)

Trust me, I’m a researcher!: The role of trust in biomedical research
af: Kerasidou, A
Udgivet: (2016)

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Udgivet: (2024-09-01)

Global disparity bias in ophthalmology artificial intelligence applications
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Algorithmic discrimination and ethical perspective of artificial intelligence /
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Udgivet: ([202)

Corrigendum: Acceptance, initial trust formation, and human biases in artificial intelligence: focus on clinicians
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Udgivet: (2022)

Data-driven research and healthcare: public trust, data governance and the NHS
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Udgivet: (2023)

What do algorithms explain? The issue of the goals and capabilities of Explainable Artificial Intelligence (XAI)
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Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research
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Before and beyond trust: reliance in medical AI
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On the practical, ethical, and legal necessity of clinical Artificial Intelligence explainability: an examination of key arguments
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Ethics in Artificial Intelligence: Toward Foundations for Global Policy
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Udgivet: (2022)

COVID-19 pandemic and artificial intelligence: challenges of ethical bias and trustworthy reliable reproducibility?
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Udgivet: (2021-03-01)

Editorial: Explainable artificial intelligence
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Explainable Artificial Intelligence in education
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Udgivet: (2022-01-01)

“I don’t think people are ready to trust these algorithms at face value”: trust and the use of machine learning algorithms in the diagnosis of rare disease
af: Nina Hallowell, et al.
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Trusted artificial intelligence for environmental assessments: An explainable high-precision model with multi-source big data
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Global gene network exploration based on explainable artificial intelligence approach.
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Data-driven research and healthcare: public trust, data governance and the NHS
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Considerations for addressing bias in artificial intelligence for health equity
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Designing an Interpretability-Based Model to Explain the Artificial Intelligence Algorithms in Healthcare
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