Human cancer diagnosis and detection using exascale computing / edited by Kapil Joshi and Somil Kumar Gupta

Preface -- 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 -- 1.2 Literature Review -- 1.3 Methodology -- 1.4 Result and Discussion -- 1.5 Conclusion -- 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 -- 2.2 Literature Review -- 2.3 Methodology -- 2.4 Results and Discussion -- 2.5 Conclusion -- 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 -- 3.2 Literature Review -- 3.3 Methodology -- 3.4 Result and Discussion -- 3.5 Conclusion -- 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 -- 4.2 Literature Review -- 4.3 Methodology -- 4.4 Results and Discussion -- 4.5 Conclusion -- 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 -- 5.2 Literature Review -- 5.3 Research Methodology -- 5.4 Results -- 5.5 Conclusion -- 5.6 Future Research Directions -- 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 -- 6.2 Literature Review -- 6.3 Research Methodology -- 6.4 Results and Discussion -- 6.5 Conclusion -- 6.6 Future Research Direction -- 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 -- 7.2 Literature Review -- 7.3 Research Methodology -- 7.4 Results and Discussion -- 7.5 Implications -- 7.6 Conclusion -- 7.7 Future Research Directions -- 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 -- 8.2 Literature Review -- 8.3 Research Methodology -- 8.4 Analysis and Discussion -- 8.5 Conclusion -- 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 -- 9.2 Literature Review -- 9.3 Methodology -- 9.4 Analysis and Discussion -- 9.5 Conclusion -- 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 -- 10.2 Literature Review -- 10.3 Research Methodology -- 10.4 Analysis and Discussion -- 10.5 Conclusion -- 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 -- 11.2 Literature Review -- 11.3 Research Methodology -- 11.4 Results and Discussion -- 11.5 Conclusion -- 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 -- 12.2 Literature Review -- 12.3 Research Methodology -- 12.4 Results and Discussion -- 12.5 Challenges -- 12.6 Conclusion -- 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 -- 13.2 Literature Review -- 13.3 Materials and Method -- 13.4 Result and Discussion -- 13.5 Conclusion -- 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 -- 14.2 Literature Review -- 14.3 Research Methodology -- 14.4 Analysis and Discussion -- 14.5 Conclusion -- 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 -- 15.2 Literature Review -- 15.3 Research Methodology -- 15.4 Analysis and Discussion -- 15.5 Conclusion -- 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 -- 16.2 Pre-Processing -- 16.3 Segmentation -- 16.4 Feature Extraction -- 16.5 SVM Classifier -- 16.6 Methodology -- 16.7 Conclusion -- 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 -- 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 -- 18 Exascale Computing: The Next Frontier of High-Performance Computing 279 Rashmi M., Girija D.K. and Yogeesh N. -- 18.1 Introduction -- 18.2 Exascale Computing -- 18.3 Exascale Computing Challenges -- 18.4 Future Lookup -- 18.5 Conclusion -- References -- Index

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

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