Intelligent Computing in Carcinogenic Disease Detection

• Autore: Das Sharma Kaushik
• Pubblicazione: Singapore : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (189 pages)
• Altri autori: KarSubhajit MaitraMadhubanti
• Nota di contenuto: Intro -- Preface -- Contents -- List of Abbreviations -- 1 Introduction -- 1.1 Introduction -- 1.2 Historical Background of Carcinogenic Disease Detection -- 1.3 Intelligent Computing Tools in Carcinogenic Disease Detection and Classification -- 1.3.1 Image Processing Tools -- 1.3.2 Machine Learning Tools -- 1.3.2.1 Supervised Learning and Unsupervised Learning -- 1.3.2.2 Cross-Validation and Blind Test -- 1.3.2.3 Filter and Wrapper Methods -- 1.3.3 Modern Optimization Tools -- 1.4 Organization of the Book -- 1.5 Summary -- References -- 2 Biological Background of Benchmark Carcinogenic Data Sets -- 2.1 Introduction -- 2.2 Benchmark Carcinogenic Data Set I -- 2.2.1 Mathematical Representation of Microarray Gene Expression Data -- 2.2.2 Benchmark Microarray Gene Expression Data Sets -- 2.3 Benchmark Carcinogenic Data Set II -- 2.3.1 Microscopic Blood Smear Images -- 2.4 Benchmark Carcinogenic Data Set III -- 2.4.1 CT Images -- 2.5 Summary -- References -- 3 Intelligent Computing Approaches for Carcinogenic Disease Detection: A Review -- 3.1 Introduction -- 3.2 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set I -- 3.3 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set II -- 3.4 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set III -- 3.5 Summary -- References -- 4 Classical Approaches in Gene Evaluation for Carcinogenic Disease Detection -- 4.1 Introduction -- 4.2 Filter Approaches in Gene Evaluation -- 4.2.1 T-Test Technique -- 4.2.2 Chi-Square Technique -- 4.2.3 Signal-to-Noise Ratio Technique -- 4.3 Wrapper Approaches in Gene Evaluation -- 4.3.1 Particle Swarm Optimization (PSO) -- 4.3.2 PSO-Based Wrapper Method for Gene Selection -- 4.4 Classifiers -- 4.4.1 Support Vector Machine (SVM) Classifier -- 4.4.2 k-Nearest Neighbor Classifier -- 4.5 Experimental Study. ; 4.5.1 Experimental Study on Filter Approaches -- 4.5.2 Experimental Study on Wrapper Approaches -- 4.6 Summary -- References -- 5 Intelligent Computing Approach in Gene Evaluation for Carcinogenic Disease Detection -- 5.1 Introduction -- 5.2 Adaptive k-Nearest Neighborhood Technique -- 5.2.1 PSO-Based Adaptive k-Nearest Neighborhood Technique for Gene Evaluation -- 5.2.2 Fitness Function -- 5.3 Experimental Study -- 5.4 Analysis of Experimental Results -- 5.4.1 Analysis of SRBCT Data Set -- 5.4.2 Analysis of ALL_AML Data Set -- 5.4.3 Analysis of MLL Data Set -- 5.5 Summary -- References -- 6 Intelligent Computing Approach for Leukocyte Identification -- 6.1 Introduction -- 6.2 Preprocessing -- 6.2.1 Identification of Leukocytes -- 6.2.2 Separation of Grouped Leukocytes -- 6.2.3 Image Cleaning -- 6.2.4 Separation of Whole Leukocyte, Nucleus, and Cytoplasm -- 6.3 Feature Extraction -- 6.4 Weighted Aggregation-Based Transposition PSO for Feature Evaluation -- 6.4.1 WATPSO-Based Feature Selection Technique -- 6.5 Experimental Study -- 6.5.1 Database -- 6.5.2 Performance Measure -- 6.5.3 Performance Evaluation -- 6.5.4 Comparative Study with Other Related Works Utilizing ALL Image Data -- 6.6 Summary -- References -- 7 Intelligent Computing Approach for Lung Nodule Detection -- 7.1 Introduction -- 7.2 Preprocessing -- 7.2.1 Lung Segmentation -- 7.2.2 Volumetric Shape Index -- 7.2.3 Multi-scale Dot Enhancement Filter -- 7.3 Lung Nodule Detection and Classification Methodology -- 7.3.1 Harmony Search Algorithm -- 7.3.2 Fitness Function -- 7.3.3 Adaptive Weight Selection Strategy -- 7.3.4 GrIHS-Based Feature Selection Strategy -- 7.4 Experimental Study -- 7.4.1 Result Analysis -- 7.5 Summary -- References -- 8 Conclusion -- 8.1 Future Research Directions -- Index.
• Titolo autorizzato: Intelligent Computing in Carcinogenic Disease Detection
• ISBN: 981-9724-24-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910861098403321
• Lo trovi qui: Univ. Federico II
• Serie: Computational Intelligence Methods and Applications Series