The past decade has seen a remarkable series of advances in machine learning, and in particular deep learning approaches based on artificial neural networks, to improve our abilities to build more accurate systems across a broad range of areas, including computer vision, speech recognition, language translation, and natural language understanding tasks.
“This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging”.
It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions.
We have launched, within the open publishing platform “PubPub“, a research community in English language (its equivalent in Spanish too). The benefit is based on four pillars: 1) readers, 2) authors, 3) reviewers and 4) journals. (This is based in OpenSource software). As part of the Knowledge Futures Group, we’re committed to making PubPub open …
OpenAccess Publication System: welcome to OpenScience Read More »
The structure and content of this work has been guided by the curricula developed by the European Society of Radiology, the Royal College of Radiologists, the Alliance of Medical Student Educators in Radiology, with guidance and input from Canadian Radiology Undergraduate Education Coordinators, and the Canadian Heads of Academic Radiology (CHAR).
In February 2020, the European Commission (EC) published a white paper entitled, On Artificial Intelligence – A European approach to excellence and trust. This paper outlines the EC’s policy options for the promotion and adoption of artificial intelligence (AI) in the European Union. We reviewed this paper and published a response addressing the EC’s plans to build an “ecosystem of excellence” and an “ecosystem of trust,” as well as the safety and liability implications of AI, the internet of things (IoT), and robotics.
A key challenge to making effective use of evolutionary algorithms (EAs) is to choose appropriate settings for their parameters. However, the appropriate parameter setting generally depends on the structure of the optimization problem, which is often unknown to the user. Non‐deterministic parameter control mechanisms adjust parameters using information obtained from the evolutionary process.
