03361nam a22005175i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001800172072001600190072002300206072001500229100008800244245011000332250001800442264007500460300006300535336002600598337002600624338003600650347002400686490007500710505023900785520114501024650002302169650003202192650003602224650002802260650004202288650002402330650003602354650004702390700008502437710003402522773002602556776003602582776003602618776003602654830007502690856004602765912001502811999001702826978-3-031-44877-5DE-He21320251030110840.0cr nn 008mamaa231126s2024    sz |    s    |||| 0|eng d  a97830314487759978-3-031-44877-57 a10.1007/978-3-031-44877-52doi 4aTK5101-5105.9 7aTJK2bicssc 7aTEC0410002bisacsh 7aTJK2thema1 aPrzystalski, Karol.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut96757310aExplainable Machine Learning in Medicineh[electronic resource] /cby Karol Przystalski, Rohit M. Thanki.  a1st ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024.  aXI, 82 p. 14 illus., 12 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSynthesis Lectures on Engineering, Science, and Technology,x2690-03270 a1 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.  aThis 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. 0aTelecommunication. 0aMedical informatics.960693 0aArtificial intelligence.958441 0aBiomedical engineering.14aCommunications Engineering, Networks.24aHealth Informatics.24aArtificial Intelligence.95844124aBiomedical Engineering and Bioengineering.1 aThanki, Rohit M.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9675742 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303144876808iPrinted edition:z978303144878208iPrinted edition:z9783031448799 0aSynthesis Lectures on Engineering, Science, and Technology,x2690-032740uhttps://doi.org/10.1007/978-3-031-44877-5  aZDB-2-SXSC  c56644d56644