Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
[HTML][HTML] Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical …
The emergence of Industry 4.0 marks a transformative era for businesses and industries,
characterized by advanced technologies like automation, Internet of Things (IoT), artificial …
characterized by advanced technologies like automation, Internet of Things (IoT), artificial …
Health system-scale language models are all-purpose prediction engines
Physicians make critical time-constrained decisions every day. Clinical predictive models
can help physicians and administrators make decisions by forecasting clinical and …
can help physicians and administrators make decisions by forecasting clinical and …
[HTML][HTML] Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities
Abstract Nowadays, Artificial Intelligence (AI) literacy has become an emerging topic in
digital literacy education research. However, it is still under-explored in early childhood …
digital literacy education research. However, it is still under-explored in early childhood …
[图书][B] Towards a standard for identifying and managing bias in artificial intelligence
R Schwartz, R Schwartz, A Vassilev, K Greene… - 2022 - dwt.com
As individuals and communities interact in and with an environment that is increasingly
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
Predictive artificial intelligence (AI) systems based on deep learning have been shown to
achieve expert-level identification of diseases in multiple medical imaging settings, but can …
achieve expert-level identification of diseases in multiple medical imaging settings, but can …
Automation bias in mammography: the impact of artificial intelligence BI-RADS suggestions on reader performance
Background Automation bias (the propensity for humans to favor suggestions from
automated decision-making systems) is a known source of error in human-machine …
automated decision-making systems) is a known source of error in human-machine …
Ethical, legal, and social considerations of AI-based medical decision-support tools: A scoping review
Introduction Recent developments in the field of Artificial Intelligence (AI) applied to
healthcare promise to solve many of the existing global issues in advancing human health …
healthcare promise to solve many of the existing global issues in advancing human health …
Working with AI to persuade: Examining a large language model's ability to generate pro-vaccination messages
Artificial Intelligence (AI) is a transformative force in communication and messaging strategy,
with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI …
with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI …
Ignore, trust, or negotiate: understanding clinician acceptance of AI-based treatment recommendations in health care
Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …
clinician acceptance remains a critical barrier. We developed a novel decision support …