55 citations · 68 across the 8 of their papers we have counts for
9 papers
Explainable AI: Definition and attributes of a good explanation for health AI
Evangelia Kyrimi, Scott McLachlan, Jared M Wohlgemut +4
Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity…
The Self-Driving Car: Crossroads at the Bleeding Edge of Artificial Intelligence and Law
Scott McLachlan, Evangelia Kyrimi, Kudakwashe Dube +2
Artificial intelligence (AI) features are increasingly being embedded in cars and are central to the operation of self-driving cars (SDC). There is little or no effort expended tow…
Lawmaps: Enabling Legal AI development through Visualisation of the Implicit Structure of Legislation and Lawyerly Process
Scott McLachlan, Evangelia Kyrimi, Kudakwashe Dube +2
Modelling that exploits visual elements and information visualisation are important areas that have contributed immensely to understanding and the computerisation advancements in m…
Medical idioms for clinical Bayesian network development
Evangelia Kyrimi, Mariana Raniere Neves, Scott McLachlan +3
Bayesian Networks (BNs) are graphical probabilistic models that have proven popular in medical applications. While numerous medical BNs have been published, most are presented fait…
Bluetooth Smartphone Apps: Are they the most private and effective solution for COVID-19 contact tracing?
Scott McLachlan, Peter Lucas, Kudakwashe Dube +5
Many digital solutions mainly involving Bluetooth technology are being proposed for Contact Tracing Apps (CTA) to reduce the spread of COVID-19. Concerns have been raised regarding…
An Incremental Explanation of Inference in Hybrid Bayesian Networks for Increasing Model Trustworthiness and Supporting Clinical Decision Making
Evangelia Kyrimi, Somayyeh Mossadegh, Nigel Tai +1
Various AI models are increasingly being considered as part of clinical decision-support tools. However, the trustworthiness of such models is rarely considered. Clinicians are mor…