[HTML][HTML] Notions of explainability and evaluation approaches for explainable artificial intelligence

G Vilone, L Longo - Information Fusion, 2021 - Elsevier
Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …

[PDF][PDF] The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

YYM Aung, DCS Wong, DSW Ting - British medical bulletin, 2021 - academic.oup.com
Introduction Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields
in various sectors, including healthcare. This article reviews AI's present applications in …

Lack of transparency and potential bias in artificial intelligence data sets and algorithms: a scoping review

R Daneshjou, MP Smith, MD Sun… - JAMA …, 2021 - jamanetwork.com
Importance Clinical artificial intelligence (AI) algorithms have the potential to improve clinical
care, but fair, generalizable algorithms depend on the clinical data on which they are trained …

The ethics of algorithms: key problems and solutions

A Tsamados, N Aggarwal, J Cowls, J Morley… - Ethics, governance, and …, 2021 - Springer
Research on the ethics of algorithms has grown substantially over the past decade.
Alongside the exponential development and application of machine learning algorithms …

How to design AI for social good: Seven essential factors

L Floridi, J Cowls, TC King, M Taddeo - Ethics, Governance, and Policies …, 2021 - Springer
Abstract The idea of Artificial Intelligence for Social Good (henceforth AI4SG) is gaining
traction within information societies in general and the AI community in particular. It has the …

Understanding, explaining, and utilizing medical artificial intelligence

R Cadario, C Longoni, CK Morewedge - Nature human behaviour, 2021 - nature.com
Medical artificial intelligence is cost-effective and scalable and often outperforms human
providers, yet people are reluctant to use it. We show that resistance to the utilization of …

A survey on recent named entity recognition and relationship extraction techniques on clinical texts

P Bose, S Srinivasan, WC Sleeman IV, J Palta… - Applied Sciences, 2021 - mdpi.com
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …

Artificial intelligence and patient-centered decision-making

JC Bjerring, J Busch - Philosophy & technology, 2021 - Springer
Advanced AI systems are rapidly making their way into medical research and practice, and,
arguably, it is only a matter of time before they will surpass human practitioners in terms of …

A human-ai collaborative approach for clinical decision making on rehabilitation assessment

MH Lee, DP Siewiorek, A Smailagic… - Proceedings of the …, 2021 - dl.acm.org
Advances in artificial intelligence (AI) have made it increasingly applicable to supplement
expert's decision-making in the form of a decision support system on various tasks. For …

What is interpretability?

A Erasmus, TDP Brunet, E Fisher - Philosophy & Technology, 2021 - Springer
We argue that artificial networks are explainable and offer a novel theory of interpretability.
Two sets of conceptual questions are prominent in theoretical engagements with artificial …