03520nam a22005535i 4500 978-3-031-44877-5 DE-He213 20251030110840.0 cr nn 008mamaa 231126s2024 sz | s |||| 0|eng d 9783031448775 978-3-031-44877-5 10.1007/978-3-031-44877-5 doi TK5101-5105.9 TJK bicssc TEC041000 bisacsh TJK thema Przystalski, Karol. author. aut http://id.loc.gov/vocabulary/relators/aut 67573 Explainable Machine Learning in Medicine [electronic resource] / by Karol Przystalski, Rohit M. Thanki. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XI, 82 p. 14 illus., 12 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Synthesis Lectures on Engineering, Science, and Technology, 2690-0327 1 Introduction -- 2 Medical Tabular Data -- 3 Natural Language Processing for Medical Data Analysis -- 4 Computer Vision for Medical Data Analysis -- 5 Time Series Data Used for Diseases Recognition and Anomaly Detection -- 6 Summary. This book covers a variety of advanced communications technologies that can be used to analyze medical data and can be used to diagnose diseases in clinic centers. The book is a primer of methods for medicine, providing an overview of explainable artificial intelligence (AI) techniques that can be applied in different medical challenges. The authors discuss how to select and apply the proper technology depending on the provided data and the analysis desired. Because a variety of data can be used in the medical field, the book explains how to deal with challenges connected with each type. A number of scenarios are introduced that can happen in real-time environments, with each pared with a type of machine learning that can be used to solve it. Provides a detailed primer on explainable artificial intelligence (AI) and machine learning (ML) methods that can be used in medical cases Presents how explainable AI can aid in choosing ML algorithms that give better performance in medical applications Covers various kinds of medical data used to diagnose diseases in clinic centers and what technologies are best suited to analyze it. Telecommunication. Medical informatics. 60693 Artificial intelligence. 58441 Biomedical engineering. Communications Engineering, Networks. Health Informatics. Artificial Intelligence. 58441 Biomedical Engineering and Bioengineering. Thanki, Rohit M. author. aut http://id.loc.gov/vocabulary/relators/aut 67574 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031448768 Printed edition: 9783031448782 Printed edition: 9783031448799 Synthesis Lectures on Engineering, Science, and Technology, 2690-0327 https://doi.org/10.1007/978-3-031-44877-5 ZDB-2-SXSC 56644 56644