03814nam a22005655i 4500 978-981-97-2424-6 DE-He213 20251030112047.0 cr nn 008mamaa 240517s2024 si | s |||| 0|eng d 9789819724246 978-981-97-2424-6 10.1007/978-981-97-2424-6 doi Q336 UN bicssc COM021000 bisacsh UN thema Das Sharma, Kaushik. author. aut http://id.loc.gov/vocabulary/relators/aut 76970 Intelligent Computing in Carcinogenic Disease Detection [electronic resource] / by Kaushik Das Sharma, Subhajit Kar, Madhubanti Maitra. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XIV, 180 p. 88 illus., 35 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Computational Intelligence Methods and Applications, 2510-1773 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. Artificial intelligence Data processing. Computer science. 58552 Engineering Data processing. Data Science. Theory and Algorithms for Application Domains. 67030 Data Engineering. 66059 Kar, Subhajit. author. aut http://id.loc.gov/vocabulary/relators/aut 76971 Maitra, Madhubanti. author. aut http://id.loc.gov/vocabulary/relators/aut 76972 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819724239 Printed edition: 9789819724253 Printed edition: 9789819724260 Computational Intelligence Methods and Applications, 2510-1773 70583 https://doi.org/10.1007/978-981-97-2424-6 ZDB-2-SCS ZDB-2-SXCS 59932 59932