{"product_id":"human-cancer-diagnosis-and-detection-using-exascale-computing-hardback-9781394197675","title":"Human Cancer Diagnosis and Detection Using Exascale Computing (Hardback) 9781394197675","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eHuman Cancer Diagnosis and Detection Using Exascale Computing\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eKapil Joshi (Edited by), Joshi (Author), Somil Kumar Gupta (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394197675, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 23 February 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e336 pages\u003cbr\u003e22.9 x 15.2 x 2.1 cm, 0.78 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eHuman Cancer Diagnosis and Detection Using Exascale Computing\u003c\/b\u003e \u003cp\u003e \u003cb\u003eThe 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. \u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eExascale 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.  \u003c\/p\u003e\n\u003cp\u003eThe 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.  \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eAudience \u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThis 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Evaluating the Impact of Healthcare 4.0 on the Performance of Hospitals 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePramod Kumar, Nitu Maurya, Keerthiraj, Somanchi Hari Krishna, Geetha Manoharan and Anupama Bharti\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Literature Review 4\u003c\/p\u003e \u003cp\u003e1.3 Methodology 6\u003c\/p\u003e \u003cp\u003e1.3.1 Selection of the Sample and Characterization 6\u003c\/p\u003e \u003cp\u003e1.3.2 Creation of a Data-Gathering Tool and Measures 7\u003c\/p\u003e \u003cp\u003e1.3.3 Inspection of the Conceptions’ Reliability and Validity 8\u003c\/p\u003e \u003cp\u003e1.3.4 Data Evaluation 8\u003c\/p\u003e \u003cp\u003e1.4 Result and Discussion 9\u003c\/p\u003e \u003cp\u003e1.5 Conclusion 11\u003c\/p\u003e \u003cp\u003eReferences 12\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Human Breast Cancer Classification Employing the Machine Learning Ensemble 19\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSreenivas Mekala, S. Srinivasulu Raju, M. Gomathi, Naga Venkateshwara Rao K., Kothandaraman D. and Saurabh Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 20\u003c\/p\u003e \u003cp\u003e2.1.1 Breast Cancer Symptoms and Signs 20\u003c\/p\u003e \u003cp\u003e2.1.2 Breast Cancer Risk Factors 21\u003c\/p\u003e \u003cp\u003e2.1.3 Disease Prediction Using Machine Learning 22\u003c\/p\u003e \u003cp\u003e2.2 Literature Review 22\u003c\/p\u003e \u003cp\u003e2.3 Methodology 24\u003c\/p\u003e \u003cp\u003e2.3.1 Bayesian Network 24\u003c\/p\u003e \u003cp\u003e2.3.2 Radial Basis Function 25\u003c\/p\u003e \u003cp\u003e2.3.3 Ensemble Learning 26\u003c\/p\u003e \u003cp\u003e2.3.4 The Suggested Algorithm 27\u003c\/p\u003e \u003cp\u003e2.4 Results and Discussion 28\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 31\u003c\/p\u003e \u003cp\u003eReferences 31\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Multi-Objective Differential Development Using DNN for Multimodality Medical Image Fusion 35\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Ranjith Kumar, Abhishek Dondapati, Dilip Kumar Sharma, Prakash Pareek, Rajchandar K. and S. Shalini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 36\u003c\/p\u003e \u003cp\u003e3.2 Literature Review 37\u003c\/p\u003e \u003cp\u003e3.3 Methodology 38\u003c\/p\u003e \u003cp\u003e3.3.1 Non-Subsampled Contourlet Transform 40\u003c\/p\u003e \u003cp\u003e3.3.2 Deep Xception Mode Feature Extraction 40\u003c\/p\u003e \u003cp\u003e3.3.3 Differential Evolutions with Several Objectives for Feature Selection 41\u003c\/p\u003e \u003cp\u003e3.3.4 Fusion of High-Frequency Bands 41\u003c\/p\u003e \u003cp\u003e3.4 Result and Discussion 41\u003c\/p\u003e \u003cp\u003e3.4.1 Visual Evaluation 41\u003c\/p\u003e \u003cp\u003e3.4.2 Quantitative Research 43\u003c\/p\u003e \u003cp\u003e3.5 Conclusion 47\u003c\/p\u003e \u003cp\u003eReferences 47\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Multimodal Deep Learning Analysis for Biomedical Data Fusion 53\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDivyanshu Sinha, B. Jogeswara Rao, D. Khalandar Basha, Parvathapuram Pavan Kumar, N. Shilpa and Saurabh Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 54\u003c\/p\u003e \u003cp\u003e4.2 Literature Review 56\u003c\/p\u003e \u003cp\u003e4.3 Methodology 58\u003c\/p\u003e \u003cp\u003e4.3.1 Early Fusion 59\u003c\/p\u003e \u003cp\u003e4.3.2 Intermediate Fusion 60\u003c\/p\u003e \u003cp\u003e4.3.3 Late Fusion 62\u003c\/p\u003e \u003cp\u003e4.4 Results and Discussion 62\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 64\u003c\/p\u003e \u003cp\u003eReferences 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Developing Robot-Based Neurorehabilitation Exercises Using a Teaching–Training Process 71\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eW. Vinu, Sonali Vyas, A. Chandrashekhar, T. Ch. Anil Kumar, T. Raghu and Mohit Tiwari\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 72\u003c\/p\u003e \u003cp\u003e5.1.1 Research Gap 74\u003c\/p\u003e \u003cp\u003e5.1.2 Research Aim 74\u003c\/p\u003e \u003cp\u003e5.2 Literature Review 74\u003c\/p\u003e \u003cp\u003e5.3 Research Methodology 77\u003c\/p\u003e \u003cp\u003e5.4 Results 78\u003c\/p\u003e \u003cp\u003e5.5 Conclusion 81\u003c\/p\u003e \u003cp\u003e5.6 Future Research Directions 82\u003c\/p\u003e \u003cp\u003eReferences 83\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Investigation on Introduction to Heterogeneous Exascale Computing in the Medical Field 87\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Pyingkodi, Raju Shanmugam, Dilip Kumar Sharma, Deepesh Lall, S. Deepan and B. Dasu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 88\u003c\/p\u003e \u003cp\u003e6.1.1 Research Gap 89\u003c\/p\u003e \u003cp\u003e6.2 Literature Review 89\u003c\/p\u003e \u003cp\u003e6.3 Research Methodology 92\u003c\/p\u003e \u003cp\u003e6.4 Results and Discussion 94\u003c\/p\u003e \u003cp\u003e6.5 Conclusion 96\u003c\/p\u003e \u003cp\u003e6.6 Future Research Direction 96\u003c\/p\u003e \u003cp\u003eReferences 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Adoption of Cloud Computing in the Healthcare Field Using the SEM Approach 101\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eR. Chithambaramani, C. Balakumar, Dilip Kumar Sharma, Keyur Patel, Bhavana Jamalpur and M. R. Arun\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 102\u003c\/p\u003e \u003cp\u003e7.1.1 Research Gap 103\u003c\/p\u003e \u003cp\u003e7.1.2 Research Aim 103\u003c\/p\u003e \u003cp\u003e7.2 Literature Review 104\u003c\/p\u003e \u003cp\u003e7.3 Research Methodology 106\u003c\/p\u003e \u003cp\u003e7.3.1 Research Hypothesis 107\u003c\/p\u003e \u003cp\u003e7.3.2 Data Analysis 107\u003c\/p\u003e \u003cp\u003e7.4 Results and Discussion 107\u003c\/p\u003e \u003cp\u003e7.5 Implications 110\u003c\/p\u003e \u003cp\u003e7.6 Conclusion 110\u003c\/p\u003e \u003cp\u003e7.7 Future Research Directions 111\u003c\/p\u003e \u003cp\u003eReferences 112\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Chest X-Ray Analysis for COVID-19 Diagnosis Using an Exascale Computation and Machine Learning Framework 115\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Dhinakaran, S. Deivasigamani, Saikat Kar, Nishakar Kankalla, V. Malathy and Saurabh Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 116\u003c\/p\u003e \u003cp\u003e8.2 Literature Review 117\u003c\/p\u003e \u003cp\u003e8.3 Research Methodology 119\u003c\/p\u003e \u003cp\u003e8.4 Analysis and Discussion 120\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 130\u003c\/p\u003e \u003cp\u003eReferences 131\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 3D-Printed Human Organ Designs with Tissue Physical Characteristics and Embedded Sensors 135\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eA. Chandrashekhar, R. Raffik, R. Sridevi, M. Sindhu, Kodela Rajkumar and Tarun Jaiswal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 136\u003c\/p\u003e \u003cp\u003e9.2 Literature Review 137\u003c\/p\u003e \u003cp\u003e9.3 Methodology 139\u003c\/p\u003e \u003cp\u003e9.4 Analysis and Discussion 140\u003c\/p\u003e \u003cp\u003e9.5 Conclusion 149\u003c\/p\u003e \u003cp\u003eReferences 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Fast Computing Network Infrastructure for Healthcare Systems Based on 6G Future Perspective 153\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRanjeet Yadav, S. L. Prathapa Reddy, Akshay Upmanyu, Ravi Kumar Sanapala, V. Malathy and Umakant Bhaskar Gohatre\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 154\u003c\/p\u003e \u003cp\u003e10.2 Literature Review 155\u003c\/p\u003e \u003cp\u003e10.3 Research Methodology 157\u003c\/p\u003e \u003cp\u003e10.4 Analysis and Discussion 158\u003c\/p\u003e \u003cp\u003e10.5 Conclusion 167\u003c\/p\u003e \u003cp\u003eReferences 168\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning 171\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eG. Santhakumar, Dattatray G. Takale, Swati Tyagi, Raju Anitha, Mohit Tiwari and Joshuva Arockia Dhanraj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 172\u003c\/p\u003e \u003cp\u003e11.1.1 Research Gap 174\u003c\/p\u003e \u003cp\u003e11.1.2 Research Aim 174\u003c\/p\u003e \u003cp\u003e11.2 Literature Review 174\u003c\/p\u003e \u003cp\u003e11.3 Research Methodology 176\u003c\/p\u003e \u003cp\u003e11.4 Results and Discussion 177\u003c\/p\u003e \u003cp\u003e11.5 Conclusion 180\u003c\/p\u003e \u003cp\u003eReferences 181\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 New Perspectives, Challenges, and Advances in Data Fusion in Neuroimaging 185\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePedada Sujata, Dattatray G. Takale, Swati Tyagi, Saniya Bhalerao, Mohit Tiwari and Joshuva Arockia Dhanraj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 186\u003c\/p\u003e \u003cp\u003e12.1.1 Research Gap 188\u003c\/p\u003e \u003cp\u003e12.2 Literature Review 188\u003c\/p\u003e \u003cp\u003e12.3 Research Methodology 190\u003c\/p\u003e \u003cp\u003e12.3.1 Human Brain Temporal and Spatial Data Mining Using FOCA and Data Fusion 190\u003c\/p\u003e \u003cp\u003e12.3.2 Construction of the Multimodal Neuroimaging Data Fusion 190\u003c\/p\u003e \u003cp\u003e12.4 Results and Discussion 191\u003c\/p\u003e \u003cp\u003e12.4.1 EEG–fMRI Shared Multimodal Simulation Evaluation 192\u003c\/p\u003e \u003cp\u003e12.4.2 Implementation of Multimodal Neuroimaging Data Fusion 192\u003c\/p\u003e \u003cp\u003e12.5 Challenges 194\u003c\/p\u003e \u003cp\u003e12.6 Conclusion 195\u003c\/p\u003e \u003cp\u003eReferences 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 The Potential of Cloud Computing in Medical Big Data Processing Systems 199\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eA. Mallareddy, M. Jaiganesh, Sophia Navis Mary, Manikandan K., Umakant Bhaskar Gohatre and Joshuva Arockia Dhanraj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 200\u003c\/p\u003e \u003cp\u003e13.2 Literature Review 202\u003c\/p\u003e \u003cp\u003e13.3 Materials and Method 203\u003c\/p\u003e \u003cp\u003e13.4 Result and Discussion 206\u003c\/p\u003e \u003cp\u003e13.5 Conclusion 210\u003c\/p\u003e \u003cp\u003eReferences 211\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Deep Learning (DL) on Exascale Computing to Speed Up Cancer Investigation 215\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eD. Rubidha Devi, S. Ashwini, Samreen Rizvi, P. Venkata Hari Prasad, Mohit Tiwari and Joshuva Arockia Dhanraj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 216\u003c\/p\u003e \u003cp\u003e14.2 Literature Review 217\u003c\/p\u003e \u003cp\u003e14.3 Research Methodology 219\u003c\/p\u003e \u003cp\u003e14.4 Analysis and Discussion 220\u003c\/p\u003e \u003cp\u003e14.5 Conclusion 223\u003c\/p\u003e \u003cp\u003eReferences 224\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Current Breakthroughs and Future Perspectives in Surgery Based on AI-Based Computing Vision 227\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSuneet Gupta, Madhu Kumar Vanteru, Sanjeevkumar Angadi, Manikandan K., Mohit Tiwari and Joshuva Arockia Dhanraj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 228\u003c\/p\u003e \u003cp\u003e15.2 Literature Review 229\u003c\/p\u003e \u003cp\u003e15.3 Research Methodology 231\u003c\/p\u003e \u003cp\u003e15.4 Analysis and Discussion 232\u003c\/p\u003e \u003cp\u003e15.5 Conclusion 235\u003c\/p\u003e \u003cp\u003eReferences 236\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 MRI-Based Brain Tumor Detection Using Machine Learning 239\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVivek Kumar, Pinki Chugh, Bhuprabha Bharti, Anchit Bijalwan, Amrendra Tripathi, Ram Narayan and Kapil Joshi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 240\u003c\/p\u003e \u003cp\u003e16.2 Pre-Processing 242\u003c\/p\u003e \u003cp\u003e16.3 Segmentation 243\u003c\/p\u003e \u003cp\u003e16.4 Feature Extraction 244\u003c\/p\u003e \u003cp\u003e16.5 SVM Classifier 246\u003c\/p\u003e \u003cp\u003e16.6 Methodology 248\u003c\/p\u003e \u003cp\u003e16.7 Conclusion 249\u003c\/p\u003e \u003cp\u003eReferences 249\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 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\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRachana Joshi, Narinder Kumar, B. S. Rawat, Reena Dhyani, Hemlata Sharma and Rajiv Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 254\u003c\/p\u003e \u003cp\u003e17.2 Machine Learning Technique 255\u003c\/p\u003e \u003cp\u003e17.3 Composition Profile 255\u003c\/p\u003e \u003cp\u003e17.4 Reactions of Phytochemicals to Drying and Ripening 256\u003c\/p\u003e \u003cp\u003e17.5 Antioxidant Activity 257\u003c\/p\u003e \u003cp\u003e17.6 Anticancer Activity 258\u003c\/p\u003e \u003cp\u003e17.7 Activities that are Anti-Inflammatory and Relieve Pain 260\u003c\/p\u003e \u003cp\u003e17.8 Activities Controlling Diabetes and Hyperglycemia 260\u003c\/p\u003e \u003cp\u003e17.9 The Impacts of Anticholesteremic Activity on Lipid Metabolism 262\u003c\/p\u003e \u003cp\u003e17.10 Anticlotting Effect 262\u003c\/p\u003e \u003cp\u003e17.11 Antimicrobial Activity 263\u003c\/p\u003e \u003cp\u003e17.12 Immune Checkpoint Signaling 263\u003c\/p\u003e \u003cp\u003e17.13 Suppression of Antitumor Immune Response 264\u003c\/p\u003e \u003cp\u003e17.14 Antigen Masking 264\u003c\/p\u003e \u003cp\u003e17.15 Immune-Based Cancer Therapies 264\u003c\/p\u003e \u003cp\u003e17.16 Other Miscellaneous Medicinal Values 265\u003c\/p\u003e \u003cp\u003e17.17 Conclusion 267\u003c\/p\u003e \u003cp\u003eReferences 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Exascale Computing: The Next Frontier of High-Performance Computing 279\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRashmi M., Girija D.K. and Yogeesh N.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 280\u003c\/p\u003e \u003cp\u003e18.1.1 Literature Study 281\u003c\/p\u003e \u003cp\u003e18.2 Exascale Computing 282\u003c\/p\u003e \u003cp\u003e18.2.1 Exascale Computers 283\u003c\/p\u003e \u003cp\u003e18.2.2 Case Study 284\u003c\/p\u003e \u003cp\u003e18.2.3 Measuring Computer Speed 285\u003c\/p\u003e \u003cp\u003e18.2.4 Usage of FLOPS in Supercomputers 286\u003c\/p\u003e \u003cp\u003e18.2.5 Exascale Computing: A Crucial Technology 290\u003c\/p\u003e \u003cp\u003e18.2.6 Requirements of High-Speed Computers 291\u003c\/p\u003e \u003cp\u003e18.2.7 Milestones 292\u003c\/p\u003e \u003cp\u003e18.2.8 Exascale Computing Processing 293\u003c\/p\u003e \u003cp\u003e18.2.9 Advantages of Exascale Computing 294\u003c\/p\u003e \u003cp\u003e18.2.10 Exascale Computing in Various Domains 295\u003c\/p\u003e \u003cp\u003e18.2.11 Exascale Computer: A Supercomputer 297\u003c\/p\u003e \u003cp\u003e18.2.12 Exascale Computing Different from Quantum Computing 298\u003c\/p\u003e \u003cp\u003e18.3 Exascale Computing Challenges 299\u003c\/p\u003e \u003cp\u003e18.4 Future Lookup 301\u003c\/p\u003e \u003cp\u003e18.4.1 Needed Improvements 301\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 302\u003c\/p\u003e \u003cp\u003eReferences 303\u003c\/p\u003e \u003cp\u003eIndex 305\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Medicine: general issues [\u003ca title=\"See our other books on Medicine: general issues\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Medicine:%20general%20issues%20%5BMB%5D%22\"\u003eMB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433201496344,"sku":"9781394197675","price":136.46,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394197675.jpg?v=1784851573","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/human-cancer-diagnosis-and-detection-using-exascale-computing-hardback-9781394197675","provider":"Freshly Printed Books","version":"1.0","type":"link"}