Information Technology in Biomedicine

• Corporate Author: SpringerLink (Online service)
• Other Authors: Pietka, Ewa (Editor, http://id.loc.gov/vocabulary/relators/edt), Badura, Pawel (Editor, http://id.loc.gov/vocabulary/relators/edt), Kawa, Jacek (Editor, http://id.loc.gov/vocabulary/relators/edt), Wieclawek, Wojciech (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Advances in Intelligent Systems and Computing, 1011
• Subjects: Computational intelligence.; Biomedical engineering.; Health informatics.; Artificial intelligence.; Computational Intelligence.; Biomedical Engineering and Bioengineering.; Health Informatics.; Artificial Intelligence.
• Physical Description: XII, 653 p. 264 illus., 202 illus. in color. online resource.
• ISBN: 9783030237622
• ISSN: 2194-5357 ;
• DOI: 10.1007/978-3-030-23762-2

This book provides a comprehensive overview of advances in the field of medical data science, presenting carefully selected articles by leading information technology experts. Information technology, as a rapidly evolving discipline in medical data science, with significant potential in future healthcare, and multimodal acquisition systems, mobile devices, sensors, and AI-powered applications has redefined the optimization of clinical processes. This book features an interdisciplinary collection of papers that have both theoretical and applied dimensions, and includes the following sections: Medical Data Science Quantitative Data Analysis in Medical Diagnosis Data Mining Tools and Methods in Medical Applications Image Analysis Analytics in Action on SAS Platform Biocybernetics in Physiotherapy Signal Processing and Analysis Medical Tools & Interfaces Biomechanics and Biomaterials. As such, it is a valuable reference tool for scientists designing and implementing information processing tools used in systems that assist clinicians in patient care. It is also useful for students interested in innovations in quantitative medical data analysis, data mining, and artificial intelligence.