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  <titleInfo>
    <title>Explainable Machine Learning in Medicine</title>
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    <namePart>Przystalski, Karol.</namePart>
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    <namePart>Thanki, Rohit M.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>XI, 82 p. 14 illus., 12 illus. in color. online resource.</extent>
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  <abstract>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.</abstract>
  <tableOfContents>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.</tableOfContents>
  <note type="statement of responsibility">by Karol Przystalski, Rohit M. Thanki.</note>
  <subject authority="lcsh">
    <topic>Telecommunication</topic>
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    <topic>Medical informatics</topic>
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    <topic>Artificial intelligence</topic>
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  <subject authority="lcsh">
    <topic>Biomedical engineering</topic>
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  <subject>
    <topic>Communications Engineering, Networks</topic>
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  <subject>
    <topic>Health Informatics</topic>
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  <subject>
    <topic>Artificial Intelligence</topic>
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  <subject>
    <topic>Biomedical Engineering and Bioengineering</topic>
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  <identifier type="isbn">9783031448775</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-44877-5</identifier>
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