Titlebook: Artificial Intelligence in Medicine; 17th Conference on A David Riaño,Szymon Wilk,Annette ten Teije Conference proceedings 2019 Springer Na

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Mammogram Classification with Ordered Loss to perform a binary classification, by joining several severities into one positive class. In such scenarios with mixed gradings, a reliable classifier would make less mistakes between distant severities such as missing a true cancer case and calling it as normal or vise versa. To this end, we sugg

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Agent-Based Models and Spatial Enablement: A Simulation Tool to Improve Health and Wellbeing in Big policy makers have to deal with raising socioeconomic disparities and need for environmental interventions to reduce pollution and improve wellbeing. The PULSE project, funded by the EU commission under the H2020 program, aims at providing an instrument that assesses health and wellbeing in cities t

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Towards Health 4.0: e-Hospital Proposal Based Industry 4.0 and Artificial Intelligence Conceptslopment of the healthcare area, that is fundamental in life quality enhancement. This article has as objective the utilization of AI and Industry 4.0 concepts oriented to the optimization of a hospital, using a case study an Emergency Department (ED). This proposal allows the development of a curren

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Automatic Alignment of Surgical Videos Using Kinematic Datae. With the advent of Operation Room 2.0, recording video, kinematic and many other types of data during the surgery became an easy task, thus allowing artificial intelligence systems to be deployed and used in surgical and medical practice. Recently, surgical videos has been shown to provide a stru

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Mammogram Classification with Ordered Lossograms, with a large set of nearly 2,500 biopsy proven cancer cases. Evaluation of our proposed loss function showed a reduction in severe errors of missing true cancers, while preserving overall classification performance in the original task.