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Intelligent computing in carcinogenic disease detection

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent computing in carcinogenic disease detectionby Kaushik Das Sharma, Subhajit Kar, Madhubanti Maitra.
Author:	Das Sharma, Kaushik.
other author:	Kar, Subhajit.
Published:	Singapore :Springer Nature Singapore :2024.
Description:	xiv, 180 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	CancerDiagnosis
Online resource:	https://doi.org/10.1007/978-981-97-2424-6
ISBN:	9789819724246$q(electronic bk.)

Intelligent computing in carcinogenic disease detection
Das Sharma, Kaushik.

Intelligent computing in carcinogenic disease detection[electronic resource] /by Kaushik Das Sharma, Subhajit Kar, Madhubanti Maitra. - Singapore :Springer Nature Singapore :2024. - xiv, 180 p. :ill., digital ;24 cm. - Computational intelligence methods and applications,2510-1773. - Computational intelligence methods and applications..

Chapter 1. Introduction -- Chapter 2. Biological Background of Benchmark Carcinogenic Data Sets -- Chapter 3. Intelligent Computing Approaches for Carcinogenic Disease Detection: A Review -- Chapter 4. Classical Approaches in Gene Evaluation for Carcinogenic Disease Detection -- Chapter 5. Intelligent Computing Approach in Gene Evaluation for Carcinogenic Disease Detection -- Chapter 6. Intelligent Computing Approach for Leukocyte Identification -- Chapter 7. Intelligent Computing Approach for Lung Nodule Detection -- Chapter 8. Conclusion -- Index.

This book draws on a range of intelligent computing methodologies to effectively detect and classify various carcinogenic diseases. These methodologies, which have been developed on a sound foundation of gene-level, cell-level and tissue-level carcinogenic datasets, are discussed in Chapters 1 and 2. Chapters 3, 4 and 5 elaborate on several intelligent gene selection methodologies such as filter methodologies and wrapper methodologies. In addition, various gene selection philosophies for identifying relevant carcinogenic genes are described in detail. In turn, Chapters 6 and 7 tackle the issues of using cell-level and tissue-level datasets to effectively detect carcinogenic diseases. The performance of different intelligent feature selection techniques is evaluated on cell-level and tissue-level datasets to validate their effectiveness in the context of carcinogenic disease detection. In closing, the book presents illustrative case studies that demonstrate the value of intelligent computing strategies.

ISBN: 9789819724246$q(electronic bk.)

Standard No.: 10.1007/978-981-97-2424-6doiSubjects--Topical Terms:

877016
Cancer
--Diagnosis

LC Class. No.: RC270

Dewey Class. No.: 616.994075

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520 $a This book draws on a range of intelligent computing methodologies to effectively detect and classify various carcinogenic diseases. These methodologies, which have been developed on a sound foundation of gene-level, cell-level and tissue-level carcinogenic datasets, are discussed in Chapters 1 and 2. Chapters 3, 4 and 5 elaborate on several intelligent gene selection methodologies such as filter methodologies and wrapper methodologies. In addition, various gene selection philosophies for identifying relevant carcinogenic genes are described in detail. In turn, Chapters 6 and 7 tackle the issues of using cell-level and tissue-level datasets to effectively detect carcinogenic diseases. The performance of different intelligent feature selection techniques is evaluated on cell-level and tissue-level datasets to validate their effectiveness in the context of carcinogenic disease detection. In closing, the book presents illustrative case studies that demonstrate the value of intelligent computing strategies.
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