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Human Cancer Diagnosis and Detection Using Exascale Computing
| Human Cancer Diagnosis and Detection Using Exascale Computing |
| Autore | Joshi Kapil |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (330 pages) |
| Disciplina | 616.9940750285 |
| Altri autori (Persone) | GuptaSomil Kumar |
| Soggetto topico |
Exascale computing
Cancer - Diagnosis |
| ISBN |
9781394197705
1394197705 9781394197699 1394197691 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Evaluating the Impact of Healthcare 4.0 on the Performance of Hospitals -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 Methodology -- 1.3.1 Selection of the Sample and Characterization -- 1.3.2 Creation of a Data-Gathering Tool and Measures -- 1.3.3 Inspection of the Conceptions' Reliability and Validity -- 1.3.4 Data Evaluation -- 1.4 Result and Discussion -- 1.5 Conclusion -- References -- Chapter 2 Human Breast Cancer Classification Employing the Machine Learning Ensemble -- 2.1 Introduction -- 2.1.1 Breast Cancer Symptoms and Signs -- 2.1.2 Breast Cancer Risk Factors -- 2.1.3 Disease Prediction Using Machine Learning -- 2.2 Literature Review -- 2.3 Methodology -- 2.3.1 Bayesian Network -- 2.3.2 Radial Basis Function -- 2.3.3 Ensemble Learning -- 2.3.4 The Suggested Algorithm -- 2.4 Results and Discussion -- 2.5 Conclusion -- References -- Chapter 3 Multi-Objective Differential Development Using DNN for Multimodality Medical Image Fusion -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Methodology -- 3.3.1 Non-Subsampled Contourlet Transform -- 3.3.2 Deep Xception Mode Feature Extraction -- 3.3.3 Differential Evolutions with Several Objectives for Feature Selection -- 3.3.4 Fusion of High-Frequency Bands -- 3.4 Result and Discussion -- 3.4.1 Visual Evaluation -- 3.4.2 Quantitative Research -- 3.5 Conclusion -- References -- Chapter 4 Multimodal Deep Learning Analysis for Biomedical Data Fusion -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 Methodology -- 4.3.1 Early Fusion -- 4.3.2 Intermediate Fusion -- 4.3.3 Late Fusion -- 4.4 Results and Discussion -- 4.5 Conclusion -- References -- Chapter 5 Developing Robot-Based Neurorehabilitation Exercises Using a Teaching-Training Process -- 5.1 Introduction -- 5.1.1 Research Gap -- 5.1.2 Research Aim.
5.2 Literature Review -- 5.3 Research Methodology -- 5.4 Results -- 5.5 Conclusion -- 5.6 Future Research Directions -- References -- Chapter 6 Investigation on Introduction to Heterogeneous Exascale Computing in the Medical Field -- 6.1 Introduction -- 6.1.1 Research Gap -- 6.2 Literature Review -- 6.3 Research Methodology -- 6.4 Results and Discussion -- 6.5 Conclusion -- 6.6 Future Research Direction -- References -- Chapter 7 Adoption of Cloud Computing in the Healthcare Field Using the SEM Approach -- 7.1 Introduction -- 7.1.1 Research Gap -- 7.1.2 Research Aim -- 7.2 Literature Review -- 7.3 Research Methodology -- 7.3.1 Research Hypothesis -- 7.3.2 Data Analysis -- 7.4 Results and Discussion -- 7.5 Implications -- 7.6 Conclusion -- 7.7 Future Research Directions -- References -- Chapter 8 Chest X-Ray Analysis for COVID-19 Diagnosis Using an Exascale Computation and Machine Learning Framework -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Research Methodology -- 8.4 Analysis and Discussion -- 8.5 Conclusion -- References -- Chapter 9 3D-Printed Human Organ Designs with Tissue Physical Characteristics and Embedded Sensors -- 9.1 Introduction -- 9.2 Literature Review -- 9.3 Methodology -- 9.4 Analysis and Discussion -- 9.5 Conclusion -- References -- Chapter 10 Fast Computing Network Infrastructure for Healthcare Systems Based on 6G Future Perspective -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Research Methodology -- 10.4 Analysis and Discussion -- 10.5 Conclusion -- References -- Chapter 11 Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning -- 11.1 Introduction -- 11.1.1 Research Gap -- 11.1.2 Research Aim -- 11.2 Literature Review -- 11.3 Research Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- References. Chapter 12 New Perspectives, Challenges, and Advances in Data Fusion in Neuroimaging -- 12.1 Introduction -- 12.1.1 Research Gap -- 12.2 Literature Review -- 12.3 Research Methodology -- 12.3.1 Human Brain Temporal and Spatial Data Mining Using FOCA and Data Fusion -- 12.3.2 Construction of the Multimodal Neuroimaging Data Fusion -- 12.4 Results and Discussion -- 12.4.1 EEG-fMRI Shared Multimodal Simulation Evaluation -- 12.4.2 Implementation of Multimodal Neuroimaging Data Fusion -- 12.5 Challenges -- 12.6 Conclusion -- References -- Chapter 13 The Potential of Cloud Computing in Medical Big Data Processing Systems -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Materials and Method -- 13.4 Result and Discussion -- 13.5 Conclusion -- References -- Chapter 14 Deep Learning (DL) on Exascale Computing to Speed Up Cancer Investigation -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Research Methodology -- 14.4 Analysis and Discussion -- 14.5 Conclusion -- References -- Chapter 15 Current Breakthroughs and Future Perspectives in Surgery Based on AI-Based Computing Vision -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Research Methodology -- 15.4 Analysis and Discussion -- 15.5 Conclusion -- References -- Chapter 16 MRI-Based Brain Tumor Detection Using Machine Learning -- 16.1 Introduction -- 16.2 Pre-Processing -- 16.3 Segmentation -- 16.4 Feature Extraction -- 16.5 SVM Classifier -- 16.6 Methodology -- 16.7 Conclusion -- References -- Chapter 17 Chili Pepper as a Natural Therapeutic Drug: A Review of Its Anticancer and Antioxidant Properties and Mechanism of Action Using the Machine Learning Approach -- 17.1 Introduction -- 17.2 Machine Learning Technique -- 17.3 Composition Profile -- 17.4 Reactions of Phytochemicals to Drying and Ripening -- 17.5 Antioxidant Activity -- 17.6 Anticancer Activity. 17.7 Activities that are Anti-Inflammatory and Relieve Pain -- 17.8 Activities Controlling Diabetes and Hyperglycemia -- 17.9 The Impacts of Anticholesteremic Activity on Lipid Metabolism -- 17.10 Anticlotting Effect -- 17.11 Antimicrobial Activity -- 17.12 Immune Checkpoint Signaling -- 17.13 Suppression of Antitumor Immune Response -- 17.14 Antigen Masking -- 17.15 Immune-Based Cancer Therapies -- 17.16 Other Miscellaneous Medicinal Values -- 17.17 Conclusion -- References -- Chapter 18 Exascale Computing: The Next Frontier of High-Performance Computing -- 18.1 Introduction -- 18.1.1 Literature Study -- 18.2 Exascale Computing -- 18.2.1 Exascale Computers -- 18.2.2 Case Study -- 18.2.3 Measuring Computer Speed -- 18.2.4 Usage of FLOPS in Supercomputers -- 18.2.5 Exascale Computing: A Crucial Technology -- 18.2.6 Requirements of High-Speed Computers -- 18.2.7 Milestones -- 18.2.8 Exascale Computing Processing -- 18.2.9 Advantages of Exascale Computing -- 18.2.10 Exascale Computing in Various Domains -- 18.2.11 Exascale Computer: A Supercomputer -- 18.2.12 Exascale Computing Different from Quantum Computing -- 18.3 Exascale Computing Challenges -- 18.4 Future Lookup -- 18.4.1 Needed Improvements -- 18.5 Conclusion -- References -- Index -- EULA. |
| Record Nr. | UNINA-9911020320203321 |
Joshi Kapil
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Preparing an incompressible-flow fluid dynamics code for exascale-class wind energy simulations : preprint / / Paul Mullowney [and seven others]
| Preparing an incompressible-flow fluid dynamics code for exascale-class wind energy simulations : preprint / / Paul Mullowney [and seven others] |
| Autore | Mullowney Paul (Computational scientist) |
| Pubbl/distr/stampa | Golden, CO : , : National Renewable Energy Laboratory, , 2021 |
| Descrizione fisica | 1 online resource (12 pages) : color illustrations |
| Collana | NREL/CP |
| Soggetto topico |
Wind power plants - United States - Computer simulation
Computational fluid dynamics Exascale computing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Preparing an incompressible-flow fluid dynamics code for exascale-class wind energy simulations |
| Record Nr. | UNINA-9910717268203321 |
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Mullowney Paul (Computational scientist)
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| Golden, CO : , : National Renewable Energy Laboratory, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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