Welcome to the Library Catalog of "Dunarea de Jos" University of Galati

Explainable Machine Learning in Medicine [electronic resource] / by Karol Przystalski, Rohit M. Thanki.

By: Contributor(s): Material type: TextSeries: Synthesis Lectures on Engineering, Science, and TechnologyPublisher: Cham : Springer International Publishing : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XI, 82 p. 14 illus., 12 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031448775
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • TK5101-5105.9
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

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.

There are no comments on this title.

to post a comment.
Biblioteca Universității "Dunărea de Jos" din Galați