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020 _a9789819724246
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024 7 _a10.1007/978-981-97-2424-6
_2doi
050 4 _aQ336
072 7 _aUN
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUN
_2thema
100 1 _aDas Sharma, Kaushik.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976970
245 1 0 _aIntelligent Computing in Carcinogenic Disease Detection
_h[electronic resource] /
_cby Kaushik Das Sharma, Subhajit Kar, Madhubanti Maitra.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIV, 180 p. 88 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aComputational Intelligence Methods and Applications,
_x2510-1773
505 0 _aChapter 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.
520 _aThis 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.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aComputer science.
_958552
650 0 _aEngineering
_xData processing.
650 1 4 _aData Science.
650 2 4 _aTheory and Algorithms for Application Domains.
_967030
650 2 4 _aData Engineering.
_966059
700 1 _aKar, Subhajit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976971
700 1 _aMaitra, Madhubanti.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976972
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819724239
776 0 8 _iPrinted edition:
_z9789819724253
776 0 8 _iPrinted edition:
_z9789819724260
830 0 _aComputational Intelligence Methods and Applications,
_x2510-1773
_970583
856 4 0 _uhttps://doi.org/10.1007/978-981-97-2424-6
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
999 _c59932
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