Quang Vinh Nguyen

Simeon J. Simoff

Daniel R. Catchpoole

Paul J Kennedy

Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.

Data Driven Science for Clinically Actionable Knowledge in Diseases

Mary L. Maher

Anna Cicognani

This volume examines the issues involved in setting up and running a virtual design studio. It presents an interdisciplinary framework for organizing, running, and improving virtual design studios. Technological issues are presented in a practical context, showing how to realize each aspect of the studio. The authors also assess potential benefits, such as improved creativity and collaboration, and other areas in which our understanding needs to be furthered. Relevant software will be available on the authors website.

Simeon J. Simoff

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