Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed,…mehr
Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed, and efficiency. The fusion of exascale computing with the field of oncology has the potential to redefine the boundaries of what is possible in the fight against cancer. The book is a comprehensive exploration of this transformative unification of science, medicine, and technology. It delves deeply into the realm of exascale computing and its profound implications for cancer research and patient care. The 18 chapters are authored by experts from diverse fields who have dedicated their careers to pushing the boundaries of what is achievable in the realm of cancer diagnosis and detection. The chapters cover a wide range of topics, from the fundamentals of exascale computing and its application to cancer genomics to the development of advanced imaging techniques and machine learning algorithms. Explored is the integration of data analytics, artificial intelligence, and high-performance computing to move cancer research to the next phase and support the creation of novel medical tools and technology for the detection and diagnosis of cancer. Audience This book has a wide audience from both computer sciences (information technology, computer vision, artificial intelligence, software engineering, applied mathematics) and the medical field (biomedical engineering, bioinformatics, oncology). Researchers, practitioners and students will find this groundbreaking book novel and very useful.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Kapil Joshi is an assistant professor in the Computer Science & Engineering Department, Uttaranchal Institute of Technology in Dehradun, Uttarakhand, India. Joshi completed a PhD on the topic of Image Quality Enhancement using Fusion Techniques. He has 8 years of academic experience in his areas of interest in Operating systems, Computer Networks, Web Technology, Data Structure, and Java. He has published various patents, research papers, and two books. In 2021, he was awarded the 'Best Young Researcher' Award in Global Education and Corporate Leadership received by Life Way Tech India Pvt. Ltd. Somil Kumar Gupta is an assistant professor in the School of Computing, DIT University, Dehradun, Uttarakhand, India. He has fourteen years of experience in academics and research. He has published many research articles in reputed national and international conferences and journals. He has published more than 16 patents in the Indian Patent Office.
Inhaltsangabe
Preface xiii 1 Evaluating the Impact of Healthcare 4.0 on the Performance of Hospitals 1 Pramod Kumar, Nitu Maurya, Keerthiraj, Somanchi Hari Krishna, Geetha Manoharan and Anupama Bharti 1.1 Introduction 2 1.2 Literature Review 4 1.3 Methodology 6 1.3.1 Selection of the Sample and Characterization 6 1.3.2 Creation of a Data-Gathering Tool and Measures 7 1.3.3 Inspection of the Conceptions' Reliability and Validity 8 1.3.4 Data Evaluation 8 1.4 Result and Discussion 9 1.5 Conclusion 11 References 12 2 Human Breast Cancer Classification Employing the Machine Learning Ensemble 19 Sreenivas Mekala, S. Srinivasulu Raju, M. Gomathi, Naga Venkateshwara Rao K., Kothandaraman D. and Saurabh Sharma 2.1 Introduction 20 2.1.1 Breast Cancer Symptoms and Signs 20 2.1.2 Breast Cancer Risk Factors 21 2.1.3 Disease Prediction Using Machine Learning 22 2.2 Literature Review 22 2.3 Methodology 24 2.3.1 Bayesian Network 24 2.3.2 Radial Basis Function 25 2.3.3 Ensemble Learning 26 2.3.4 The Suggested Algorithm 27 2.4 Results and Discussion 28 2.5 Conclusion 31 References 31 3 Multi-Objective Differential Development Using DNN for Multimodality Medical Image Fusion 35 M. Ranjith Kumar, Abhishek Dondapati, Dilip Kumar Sharma, Prakash Pareek, Rajchandar K. and S. Shalini 3.1 Introduction 36 3.2 Literature Review 37 3.3 Methodology 38 3.3.1 Non-Subsampled Contourlet Transform 40 3.3.2 Deep Xception Mode Feature Extraction 40 3.3.3 Differential Evolutions with Several Objectives for Feature Selection 41 3.3.4 Fusion of High-Frequency Bands 41 3.4 Result and Discussion 41 3.4.1 Visual Evaluation 41 3.4.2 Quantitative Research 43 3.5 Conclusion 47 References 47 4 Multimodal Deep Learning Analysis for Biomedical Data Fusion 53 Divyanshu Sinha, B. Jogeswara Rao, D. Khalandar Basha, Parvathapuram Pavan Kumar, N. Shilpa and Saurabh Sharma 4.1 Introduction 54 4.2 Literature Review 56 4.3 Methodology 58 4.3.1 Early Fusion 59 4.3.2 Intermediate Fusion 60 4.3.3 Late Fusion 62 4.4 Results and Discussion 62 4.5 Conclusion 64 References 65 5 Developing Robot-Based Neurorehabilitation Exercises Using a Teaching-Training Process 71 W. Vinu, Sonali Vyas, A. Chandrashekhar, T. Ch. Anil Kumar, T. Raghu and Mohit Tiwari 5.1 Introduction 72 5.1.1 Research Gap 74 5.1.2 Research Aim 74 5.2 Literature Review 74 5.3 Research Methodology 77 5.4 Results 78 5.5 Conclusion 81 5.6 Future Research Directions 82 References 83 6 Investigation on Introduction to Heterogeneous Exascale Computing in the Medical Field 87 M. Pyingkodi, Raju Shanmugam, Dilip Kumar Sharma, Deepesh Lall, S. Deepan and B. Dasu 6.1 Introduction 88 6.1.1 Research Gap 89 6.2 Literature Review 89 6.3 Research Methodology 92 6.4 Results and Discussion 94 6.5 Conclusion 96 6.6 Future Research Direction 96 References 97 7 Adoption of Cloud Computing in the Healthcare Field Using the SEM Approach 101 R. Chithambaramani, C. Balakumar, Dilip Kumar Sharma, Keyur Patel, Bhavana Jamalpur and M. R. Arun 7.1 Introduction 102 7.1.1 Research Gap 103 7.1.2 Research Aim 103 7.2 Literature Review 104 7.3 Research Methodology 106 7.3.1 Research Hypothesis 107 7.3.2 Data Analysis 107 7.4 Results and Discussion 107 7.5 Implications 110 7.6 Conclusion 110 7.7 Future Research Directions 111 References 112 8 Chest X-Ray Analysis for COVID-19 Diagnosis Using an Exascale Computation and Machine Learning Framework 115 M. Dhinakaran, S. Deivasigamani, Saikat Kar, Nishakar Kankalla, V. Malathy and Saurabh Sharma 8.1 Introduction 116 8.2 Literature Review 117 8.3 Research Methodology 119 8.4 Analysis and Discussion 120 8.5 Conclusion 130 References 131 9 3D-Printed Human Organ Designs with Tissue Physical Characteristics and Embedded Sensors 135 A. Chandrashekhar, R. Raffik, R. Sridevi, M. Sindhu, Kodela Rajkumar and Tarun Jaiswal 9.1 Introduction 136 9.2 Literature Review 137 9.3 Methodology 139 9.4 Analysis and Discussion 140 9.5 Conclusion 149 References 150 10 Fast Computing Network Infrastructure for Healthcare Systems Based on 6G Future Perspective 153 Ranjeet Yadav, S. L. Prathapa Reddy, Akshay Upmanyu, Ravi Kumar Sanapala, V. Malathy and Umakant Bhaskar Gohatre 10.1 Introduction 154 10.2 Literature Review 155 10.3 Research Methodology 157 10.4 Analysis and Discussion 158 10.5 Conclusion 167 References 168 11 Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning 171 G. Santhakumar, Dattatray G. Takale, Swati Tyagi, Raju Anitha, Mohit Tiwari and Joshuva Arockia Dhanraj 11.1 Introduction 172 11.1.1 Research Gap 174 11.1.2 Research Aim 174 11.2 Literature Review 174 11.3 Research Methodology 176 11.4 Results and Discussion 177 11.5 Conclusion 180 References 181 12 New Perspectives, Challenges, and Advances in Data Fusion in Neuroimaging 185 Pedada Sujata, Dattatray G. Takale, Swati Tyagi, Saniya Bhalerao, Mohit Tiwari and Joshuva Arockia Dhanraj 12.1 Introduction 186 12.1.1 Research Gap 188 12.2 Literature Review 188 12.3 Research Methodology 190 12.3.1 Human Brain Temporal and Spatial Data Mining Using FOCA and Data Fusion 190 12.3.2 Construction of the Multimodal Neuroimaging Data Fusion 190 12.4 Results and Discussion 191 12.4.1 EEG-fMRI Shared Multimodal Simulation Evaluation 192 12.4.2 Implementation of Multimodal Neuroimaging Data Fusion 192 12.5 Challenges 194 12.6 Conclusion 195 References 196 13 The Potential of Cloud Computing in Medical Big Data Processing Systems 199 A. Mallareddy, M. Jaiganesh, Sophia Navis Mary, Manikandan K., Umakant Bhaskar Gohatre and Joshuva Arockia Dhanraj 13.1 Introduction 200 13.2 Literature Review 202 13.3 Materials and Method 203 13.4 Result and Discussion 206 13.5 Conclusion 210 References 211 14 Deep Learning (DL) on Exascale Computing to Speed Up Cancer Investigation 215 D. Rubidha Devi, S. Ashwini, Samreen Rizvi, P. Venkata Hari Prasad, Mohit Tiwari and Joshuva Arockia Dhanraj 14.1 Introduction 216 14.2 Literature Review 217 14.3 Research Methodology 219 14.4 Analysis and Discussion 220 14.5 Conclusion 223 References 224 15 Current Breakthroughs and Future Perspectives in Surgery Based on AI-Based Computing Vision 227 Suneet Gupta, Madhu Kumar Vanteru, Sanjeevkumar Angadi, Manikandan K., Mohit Tiwari and Joshuva Arockia Dhanraj 15.1 Introduction 228 15.2 Literature Review 229 15.3 Research Methodology 231 15.4 Analysis and Discussion 232 15.5 Conclusion 235 References 236 16 MRI-Based Brain Tumor Detection Using Machine Learning 239 Vivek Kumar, Pinki Chugh, Bhuprabha Bharti, Anchit Bijalwan, Amrendra Tripathi, Ram Narayan and Kapil Joshi 16.1 Introduction 240 16.2 Pre-Processing 242 16.3 Segmentation 243 16.4 Feature Extraction 244 16.5 SVM Classifier 246 16.6 Methodology 248 16.7 Conclusion 249 References 249 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 253 Rachana Joshi, Narinder Kumar, B. S. Rawat, Reena Dhyani, Hemlata Sharma and Rajiv Kumar 17.1 Introduction 254 17.2 Machine Learning Technique 255 17.3 Composition Profile 255 17.4 Reactions of Phytochemicals to Drying and Ripening 256 17.5 Antioxidant Activity 257 17.6 Anticancer Activity 258 17.7 Activities that are Anti-Inflammatory and Relieve Pain 260 17.8 Activities Controlling Diabetes and Hyperglycemia 260 17.9 The Impacts of Anticholesteremic Activity on Lipid Metabolism 262 17.10 Anticlotting Effect 262 17.11 Antimicrobial Activity 263 17.12 Immune Checkpoint Signaling 263 17.13 Suppression of Antitumor Immune Response 264 17.14 Antigen Masking 264 17.15 Immune-Based Cancer Therapies 264 17.16 Other Miscellaneous Medicinal Values 265 17.17 Conclusion 267 References 268 18 Exascale Computing: The Next Frontier of High-Performance Computing 279 Rashmi M., Girija D.K. and Yogeesh N. 18.1 Introduction 280 18.1.1 Literature Study 281 18.2 Exascale Computing 282 18.2.1 Exascale Computers 283 18.2.2 Case Study 284 18.2.3 Measuring Computer Speed 285 18.2.4 Usage of FLOPS in Supercomputers 286 18.2.5 Exascale Computing: A Crucial Technology 290 18.2.6 Requirements of High-Speed Computers 291 18.2.7 Milestones 292 18.2.8 Exascale Computing Processing 293 18.2.9 Advantages of Exascale Computing 294 18.2.10 Exascale Computing in Various Domains 295 18.2.11 Exascale Computer: A Supercomputer 297 18.2.12 Exascale Computing Different from Quantum Computing 298 18.3 Exascale Computing Challenges 299 18.4 Future Lookup 301 18.4.1 Needed Improvements 301 18.5 Conclusion 302 References 303 Index 305
Preface xiii 1 Evaluating the Impact of Healthcare 4.0 on the Performance of Hospitals 1 Pramod Kumar, Nitu Maurya, Keerthiraj, Somanchi Hari Krishna, Geetha Manoharan and Anupama Bharti 1.1 Introduction 2 1.2 Literature Review 4 1.3 Methodology 6 1.3.1 Selection of the Sample and Characterization 6 1.3.2 Creation of a Data-Gathering Tool and Measures 7 1.3.3 Inspection of the Conceptions' Reliability and Validity 8 1.3.4 Data Evaluation 8 1.4 Result and Discussion 9 1.5 Conclusion 11 References 12 2 Human Breast Cancer Classification Employing the Machine Learning Ensemble 19 Sreenivas Mekala, S. Srinivasulu Raju, M. Gomathi, Naga Venkateshwara Rao K., Kothandaraman D. and Saurabh Sharma 2.1 Introduction 20 2.1.1 Breast Cancer Symptoms and Signs 20 2.1.2 Breast Cancer Risk Factors 21 2.1.3 Disease Prediction Using Machine Learning 22 2.2 Literature Review 22 2.3 Methodology 24 2.3.1 Bayesian Network 24 2.3.2 Radial Basis Function 25 2.3.3 Ensemble Learning 26 2.3.4 The Suggested Algorithm 27 2.4 Results and Discussion 28 2.5 Conclusion 31 References 31 3 Multi-Objective Differential Development Using DNN for Multimodality Medical Image Fusion 35 M. Ranjith Kumar, Abhishek Dondapati, Dilip Kumar Sharma, Prakash Pareek, Rajchandar K. and S. Shalini 3.1 Introduction 36 3.2 Literature Review 37 3.3 Methodology 38 3.3.1 Non-Subsampled Contourlet Transform 40 3.3.2 Deep Xception Mode Feature Extraction 40 3.3.3 Differential Evolutions with Several Objectives for Feature Selection 41 3.3.4 Fusion of High-Frequency Bands 41 3.4 Result and Discussion 41 3.4.1 Visual Evaluation 41 3.4.2 Quantitative Research 43 3.5 Conclusion 47 References 47 4 Multimodal Deep Learning Analysis for Biomedical Data Fusion 53 Divyanshu Sinha, B. Jogeswara Rao, D. Khalandar Basha, Parvathapuram Pavan Kumar, N. Shilpa and Saurabh Sharma 4.1 Introduction 54 4.2 Literature Review 56 4.3 Methodology 58 4.3.1 Early Fusion 59 4.3.2 Intermediate Fusion 60 4.3.3 Late Fusion 62 4.4 Results and Discussion 62 4.5 Conclusion 64 References 65 5 Developing Robot-Based Neurorehabilitation Exercises Using a Teaching-Training Process 71 W. Vinu, Sonali Vyas, A. Chandrashekhar, T. Ch. Anil Kumar, T. Raghu and Mohit Tiwari 5.1 Introduction 72 5.1.1 Research Gap 74 5.1.2 Research Aim 74 5.2 Literature Review 74 5.3 Research Methodology 77 5.4 Results 78 5.5 Conclusion 81 5.6 Future Research Directions 82 References 83 6 Investigation on Introduction to Heterogeneous Exascale Computing in the Medical Field 87 M. Pyingkodi, Raju Shanmugam, Dilip Kumar Sharma, Deepesh Lall, S. Deepan and B. Dasu 6.1 Introduction 88 6.1.1 Research Gap 89 6.2 Literature Review 89 6.3 Research Methodology 92 6.4 Results and Discussion 94 6.5 Conclusion 96 6.6 Future Research Direction 96 References 97 7 Adoption of Cloud Computing in the Healthcare Field Using the SEM Approach 101 R. Chithambaramani, C. Balakumar, Dilip Kumar Sharma, Keyur Patel, Bhavana Jamalpur and M. R. Arun 7.1 Introduction 102 7.1.1 Research Gap 103 7.1.2 Research Aim 103 7.2 Literature Review 104 7.3 Research Methodology 106 7.3.1 Research Hypothesis 107 7.3.2 Data Analysis 107 7.4 Results and Discussion 107 7.5 Implications 110 7.6 Conclusion 110 7.7 Future Research Directions 111 References 112 8 Chest X-Ray Analysis for COVID-19 Diagnosis Using an Exascale Computation and Machine Learning Framework 115 M. Dhinakaran, S. Deivasigamani, Saikat Kar, Nishakar Kankalla, V. Malathy and Saurabh Sharma 8.1 Introduction 116 8.2 Literature Review 117 8.3 Research Methodology 119 8.4 Analysis and Discussion 120 8.5 Conclusion 130 References 131 9 3D-Printed Human Organ Designs with Tissue Physical Characteristics and Embedded Sensors 135 A. Chandrashekhar, R. Raffik, R. Sridevi, M. Sindhu, Kodela Rajkumar and Tarun Jaiswal 9.1 Introduction 136 9.2 Literature Review 137 9.3 Methodology 139 9.4 Analysis and Discussion 140 9.5 Conclusion 149 References 150 10 Fast Computing Network Infrastructure for Healthcare Systems Based on 6G Future Perspective 153 Ranjeet Yadav, S. L. Prathapa Reddy, Akshay Upmanyu, Ravi Kumar Sanapala, V. Malathy and Umakant Bhaskar Gohatre 10.1 Introduction 154 10.2 Literature Review 155 10.3 Research Methodology 157 10.4 Analysis and Discussion 158 10.5 Conclusion 167 References 168 11 Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning 171 G. Santhakumar, Dattatray G. Takale, Swati Tyagi, Raju Anitha, Mohit Tiwari and Joshuva Arockia Dhanraj 11.1 Introduction 172 11.1.1 Research Gap 174 11.1.2 Research Aim 174 11.2 Literature Review 174 11.3 Research Methodology 176 11.4 Results and Discussion 177 11.5 Conclusion 180 References 181 12 New Perspectives, Challenges, and Advances in Data Fusion in Neuroimaging 185 Pedada Sujata, Dattatray G. Takale, Swati Tyagi, Saniya Bhalerao, Mohit Tiwari and Joshuva Arockia Dhanraj 12.1 Introduction 186 12.1.1 Research Gap 188 12.2 Literature Review 188 12.3 Research Methodology 190 12.3.1 Human Brain Temporal and Spatial Data Mining Using FOCA and Data Fusion 190 12.3.2 Construction of the Multimodal Neuroimaging Data Fusion 190 12.4 Results and Discussion 191 12.4.1 EEG-fMRI Shared Multimodal Simulation Evaluation 192 12.4.2 Implementation of Multimodal Neuroimaging Data Fusion 192 12.5 Challenges 194 12.6 Conclusion 195 References 196 13 The Potential of Cloud Computing in Medical Big Data Processing Systems 199 A. Mallareddy, M. Jaiganesh, Sophia Navis Mary, Manikandan K., Umakant Bhaskar Gohatre and Joshuva Arockia Dhanraj 13.1 Introduction 200 13.2 Literature Review 202 13.3 Materials and Method 203 13.4 Result and Discussion 206 13.5 Conclusion 210 References 211 14 Deep Learning (DL) on Exascale Computing to Speed Up Cancer Investigation 215 D. Rubidha Devi, S. Ashwini, Samreen Rizvi, P. Venkata Hari Prasad, Mohit Tiwari and Joshuva Arockia Dhanraj 14.1 Introduction 216 14.2 Literature Review 217 14.3 Research Methodology 219 14.4 Analysis and Discussion 220 14.5 Conclusion 223 References 224 15 Current Breakthroughs and Future Perspectives in Surgery Based on AI-Based Computing Vision 227 Suneet Gupta, Madhu Kumar Vanteru, Sanjeevkumar Angadi, Manikandan K., Mohit Tiwari and Joshuva Arockia Dhanraj 15.1 Introduction 228 15.2 Literature Review 229 15.3 Research Methodology 231 15.4 Analysis and Discussion 232 15.5 Conclusion 235 References 236 16 MRI-Based Brain Tumor Detection Using Machine Learning 239 Vivek Kumar, Pinki Chugh, Bhuprabha Bharti, Anchit Bijalwan, Amrendra Tripathi, Ram Narayan and Kapil Joshi 16.1 Introduction 240 16.2 Pre-Processing 242 16.3 Segmentation 243 16.4 Feature Extraction 244 16.5 SVM Classifier 246 16.6 Methodology 248 16.7 Conclusion 249 References 249 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 253 Rachana Joshi, Narinder Kumar, B. S. Rawat, Reena Dhyani, Hemlata Sharma and Rajiv Kumar 17.1 Introduction 254 17.2 Machine Learning Technique 255 17.3 Composition Profile 255 17.4 Reactions of Phytochemicals to Drying and Ripening 256 17.5 Antioxidant Activity 257 17.6 Anticancer Activity 258 17.7 Activities that are Anti-Inflammatory and Relieve Pain 260 17.8 Activities Controlling Diabetes and Hyperglycemia 260 17.9 The Impacts of Anticholesteremic Activity on Lipid Metabolism 262 17.10 Anticlotting Effect 262 17.11 Antimicrobial Activity 263 17.12 Immune Checkpoint Signaling 263 17.13 Suppression of Antitumor Immune Response 264 17.14 Antigen Masking 264 17.15 Immune-Based Cancer Therapies 264 17.16 Other Miscellaneous Medicinal Values 265 17.17 Conclusion 267 References 268 18 Exascale Computing: The Next Frontier of High-Performance Computing 279 Rashmi M., Girija D.K. and Yogeesh N. 18.1 Introduction 280 18.1.1 Literature Study 281 18.2 Exascale Computing 282 18.2.1 Exascale Computers 283 18.2.2 Case Study 284 18.2.3 Measuring Computer Speed 285 18.2.4 Usage of FLOPS in Supercomputers 286 18.2.5 Exascale Computing: A Crucial Technology 290 18.2.6 Requirements of High-Speed Computers 291 18.2.7 Milestones 292 18.2.8 Exascale Computing Processing 293 18.2.9 Advantages of Exascale Computing 294 18.2.10 Exascale Computing in Various Domains 295 18.2.11 Exascale Computer: A Supercomputer 297 18.2.12 Exascale Computing Different from Quantum Computing 298 18.3 Exascale Computing Challenges 299 18.4 Future Lookup 301 18.4.1 Needed Improvements 301 18.5 Conclusion 302 References 303 Index 305
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