Explainable Machine Learning in Medicine / Karol Przystalski, Rohit M. Thanki
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.
| Medienart: |
Buch |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
Cham: Springer International Publishing AG ; 2024 |
| Ausgabe: |
1st ed. 2024 |
| Reihe: |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Przystalski, Karol [VerfasserIn] |
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| Links: |
Cover [lizenzpflichtig] |
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| ISBN: |
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| Umfang: |
82 Seiten |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
1871890543 |
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| 100 | 1 | |a Przystalski, Karol |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Explainable Machine Learning in Medicine |c Karol Przystalski, Rohit M. Thanki |
| 250 | |a 1st ed. 2024 | ||
| 264 | 1 | |a Cham |b Springer International Publishing AG |c 2024 | |
| 300 | |a 82 Seiten | ||
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| 490 | 0 | |a Synthesis Lectures on Engineering, Science, and Technology | |
| 505 | 8 | 0 | |a 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. |
| 520 | |a 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 | ||
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| 650 | 4 | |a Biomedizinische Technik | |
| 650 | 4 | |a COM094000 | |
| 650 | 4 | |a COMPUTERS / Computer Science | |
| 650 | 4 | |a Communications engineering / telecommunications | |
| 650 | 4 | |a Computer aided manufacture (CAM) | |
| 650 | 4 | |a Computeranwendungen in Industrie und Technologie | |
| 650 | 4 | |a Information technology: general issues | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Maschinelles Lernen | |
| 650 | 4 | |a Nachrichtententechnik, Telekommunikation | |
| 650 | 4 | |a TECHNOLOGY & ENGINEERING / Biomedical | |
| 650 | 4 | |a TECHNOLOGY & ENGINEERING / Telecommunications | |
| 700 | 1 | |a Thanki, Rohit M. |e verfasserin |4 aut | |
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