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 …
Ethics-based AI auditing: A systematic literature review on conceptualizations of ethical principles and knowledge contributions to stakeholders
This systematic literature review synthesizes the conceptualizations of ethical principles in AI
auditing literature and the knowledge contributions to the stakeholders of AI auditing. We …
auditing literature and the knowledge contributions to the stakeholders of AI auditing. We …
Understanding the impact of explanations on advice-taking: a user study for AI-based clinical Decision Support Systems
The field of eXplainable Artificial Intelligence (XAI) focuses on providing explanations for AI
systems' decisions. XAI applications to AI-based Clinical Decision Support Systems (DSS) …
systems' decisions. XAI applications to AI-based Clinical Decision Support Systems (DSS) …
An explainable artificial intelligence approach for financial distress prediction
Z Zhang, C Wu, S Qu, X Chen - Information Processing & Management, 2022 - Elsevier
External stakeholders require accurate and explainable financial distress prediction (FDP)
models. Complex machine learning algorithms offer high accuracy, but most of them lack …
models. Complex machine learning algorithms offer high accuracy, but most of them lack …
[PDF][PDF] To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods
The main objective of eXplainable Artificial Intelligence (XAI) is to provide effective
explanations for black-box classifiers. The existing literature lists many desirable properties …
explanations for black-box classifiers. The existing literature lists many desirable properties …
Auditing fairness under unawareness through counterfactual reasoning
Artificial intelligence (AI) is rapidly becoming the pivotal solution to support critical judgments
in many life-changing decisions. In fact, a biased AI tool can be particularly harmful since …
in many life-changing decisions. In fact, a biased AI tool can be particularly harmful since …
Co-design of human-centered, explainable AI for clinical decision support
eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …
techniques to extract explanations from black-box AI models and the way such explanations …
Algorithm fairness in ai for medicine and healthcare
In the current development and deployment of many artificial intelligence (AI) systems in
healthcare, algorithm fairness is a challenging problem in delivering equitable care. Recent …
healthcare, algorithm fairness is a challenging problem in delivering equitable care. Recent …
A survey on deep learning for polyp segmentation: Techniques, challenges and future trends
Early detection and assessment of polyps play a crucial role in the prevention and treatment
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …
Continuous auditing of artificial intelligence: A conceptualization and assessment of tools and frameworks
Artificial intelligence (AI), which refers to both a research field and a set of technologies, is
rapidly growing and has already spread to application areas ranging from policing to …
rapidly growing and has already spread to application areas ranging from policing to …