This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book's promise is "no math, no code"and will explain the topics in a style that is optimized for a healthcare audience.

The starting image was of a circle on a rectangle; every subsequent image was visually connected to the previous one. It was understood from the beginning that they had to use images that could be scanned from physical items they already had at home (no images from the Internet)-such as children's books, personal collections of technical manuals and assorted ephemera. The call-and-response nature of the enterprise can be appreciated in the distinctive pairs of facing pages that present themselves as you go through the bound book. To reinforce their dual roles each image appears twice in the book, once as response and again as call. One can see the resulting series of images as a closed loop with no beginning and no end. This second, expanded edition includes the entire project of 196 exchanges that make up Dumontier and Lexier's clever, competitive, and meandering loop of images. Creative people in art and design will take pleasure in browsing the book and discover formal analogies, witty poetic correspondence and dadaesque follies, which congregate to an unseen visual narrative. Truly an inspirational tool for creative activists!

Library is a collection of paintings by two of Canada s most influential contemporary artists, Michael Dumontier and Neil Farber. From the simple premise of the book title comes a series of images that are laugh-out-loud funny. A collection of book covers adorned with titles painted in simple handwritten fonts are displayed on brightly coloured hardboard. Each book forms part of an ongoing series Dumontier and Farber started in 2009. In Dumontier and Farber s Library, titles like I Lost the Human Race, Change Your Relationship to Your Unchangeable Past, and I Have a Medical Condition That Makes It So I Don t Have to Talk to You offer surprising and astute observations, all in the duo s characteristic deadpan style. The simplicity of the shapes and text evokes an immediate but lasting profundity, with each piece causing one to wonder about the thoughts that roam their consciousness, and the books that take up residence on their and our shelves. Dumontier and Farber are founding members of the influential art collective the Royal Art Lodge, and have been collaborating on art projects for more than fifteen years, exhibiting internationally. Library is playful and insightful as it pokes and prods at the human condition.

This book constitutes the refereed proceedings of the 22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020, held in Bolzano, Italy, in September 2020. The 12 full papers presented together with 7 were carefully reviewed and selected from 104 submissions. The special theme of EKAW 2020 is "Ethical and Trustworthy Knowledge Engineering". The papers cover all aspects of eliciting, acquiring, discovering, modeling, and managing knowledge and construction of knowledge-intensive systems.