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      1. Data och IT
      2. Programmeringsböcker

      Impact of Algorithmic Technologies on Healthcare

      AvParul Dubey,Mangala Madankar

      Inbunden, Engelska, 2025

      Del i serien Machine Learning in Biomedical Science and Healthcare Informatics

      2 476 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare. This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine. After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field. Audience This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.

      Produktinformation

      • Utgivningsdatum:2025-01-28
      • Vikt:794 g
      • Format:Inbunden
      • Språk:Engelska
      • Serie:Machine Learning in Biomedical Science and Healthcare Informatics
      • Antal sidor:480
      • Förlag:John Wiley & Sons Inc
      • ISBN:9781394305469

      Utforska kategorier

      • Programmeringsböcker inom Data och IT

      Mer om författaren

      Parul Dubey, PhD, is an assistant professor in the Department of Artificial Intelligence, G. H. Raisoni College of Engineering, Nagpur, India. Her academic and research focus spans various areas of computer science and IT. She has published approximately 50 works, including journal articles, conference papers, and book chapters, along with 17 Indian patents. Mangala Madankar, PhD, is the head of the Department of Artificial Intelligence at G. H. Raisoni College of Engineering, Nagpur, India. Her research interests include natural language processing, data science, big data, and information retrieval systems. She has published over 55 research papers in international journals and conferences. Pushkar Dubey, PhD, is an assistant professor and head of the Department of Management at Pandit Sundarlal Sharma (Open) University, Chhattisgarh, Bilaspur. He has published more than 70 research papers in reputed journals, secured 7 patents, and completed 5 research projects. Bui Thanh Hung, PhD, is affiliated with the Data Science Laboratory, Data Science Department, Faculty of Information Technology, Industrial University of Ho Chi Minh City, Vietnam. His research focuses on natural language processing, machine learning, machine translation, and text processing. He has published two books and approximately 40 conference papers.

      Innehållsförteckning

      • Preface xv1 Introduction to Algorithmic Health: Exploring Healthcare Through Digital Twins 1A.S. Vinay Raj, N. Gopinath, R. Anandh, M. Mohammed Jalaluddin and Lyndsay R. Buckingham1.1 Introduction 21.2 Related Works 31.3 Hardware Description 61.4 Methodology 121.5 Performance Analysis 211.6 Conclusion 222 The Digital Revolution in Healthcare 27Devanand Bhonsle, Rama Shukla, Deepshikha Sahu, Tanuja Kashyap, Monika Dewangan and Seema Mishra2.1 Introduction 272.2 Digital Technologies in the Healthcare Sector 302.3 Evolution of Digitalization in Business 312.4 Role of IoMT in Healthcare 332.5 Internet of Medical Things Devices 352.6 Security and Privacy in the Healthcare Sector 362.7 Eliminating Security and Privacy Concerns of Digitalization of the Healthcare Sector 372.8 Discussion 392.9 Future Works 392.10 Conclusion 413 Data-Driven Diagnostics: Deep Learning for Brain Tumor Classification 45Astha Pathak and Lalita Panika3.1 Introduction 453.2 Literature Review 473.3 Methodology 523.4 Result Analysis 553.5 Conclusion 574 Predictive Analysis in Patient Care 61Bolukonda Prashanth, Bandi Krishna, Rakesh Nayak, Umashankar Ghugar and Arunakranthi Godishala4.1 Introduction 624.2 Review of Predictive Analysis 684.3 Conclusion and Future 805 Leveraging Predictive Analytics: Enhancing Brain Tumor Classification with XGBoost 85Katakam Hemanvitha and Vikram Dhiman5.1 Introduction 865.2 Literature Review 875.3 Methodology 935.4 Results and Discussion 975.5 Conclusion 1006 Machine Learning in Medical Imaging Revolutionizing Lung Cancer Diagnosis: A Comparative Analysis of Convolutional Neural Networks and Vision Transformers in Medical Imaging 103Priya Parkhi, Bhagyashree Hambarde, Himesh Gangwani, Rupali Vairagade and Fred Kalombo6.1 Introduction 1046.2 Literature Review 1086.3 Description of Model 1106.4 Methodology 1136.5 Results 1186.6 Conclusion 1247 Innovations in AI and ML for Medical Imaging: An Extensive Study with an Emphasis on Face Spoofing Detection and Snooping 127Aparna Pandey, Arvind Kumar Tiwari, Harsha Nishad and Siji A. Thomas7.1 Introduction 1287.2 Artificial Intelligence as Well as Device Understandings 1327.3 Assaults Through Entrance Spoofing 1387.4 A Case Study with Real-Time Narrative: Identifying Face Spoofing in Medical Imaging 1447.5 Moral Factors to Consider 1467.6 Discussion 1497.7 Summary 1508 Progressive Growing of Generative Adversarial Networks (PGGAN) Approach to Synthesize Medical Images 157Vishal V. Raner, Amit D. Joshi, Suraj T. Sawant and Tamizharasan P. S.8.1 Introduction 1588.2 Literature Review 1608.3 Methodology 1628.4 Results and Discussion 1678.5 Conclusions 1739 Revolutionizing Healthcare Through Optimized Video Retrieval 177Pratibha Singh and Alok Kumar Singh Kushwaha9.1 Introduction 1789.2 Literature Review 1809.3 Methodology 1829.4 Results and Discussion 1849.5 Conclusion 18610 Multiclass Classification of Oral Diseases Using Deep Learning Models 189Mohammed Zubair Hussain, Shrey Gupta, Bhagyashree Hambarde, Priya Parkhi and Zafar Karimov10.1 Introduction 19010.2 Literature Review 19110.3 Methodology 19310.4 Results 20210.5 Conclusion 20511 Smart Wearable Devices for Remote Patient Monitoring in Healthcare 209Ravi Mishra, Swati Chaitandas Hadke, Devanand Bhonsle, Priti Nilesh Bhagat, Anupama Mahabansi and Sheetal Mungale11.1 Introduction 21011.2 Wearable Devices for Remote Monitoring 21311.3 Communication Technologies for Remote Healthcare Monitoring 21811.4 Proposed Methodology 21911.5 Conclusion 22112 Efficient IoT Solutions for Remote Health Monitoring 225Vijayakumar S., N. Sheik Hameed, Kanchan S. Tiwari, A. Allwyn Sundarraj, N. Gopinath and Lyndsay R. Buckingham12.1 Introduction 22612.2 Related Works 22812.3 Methodology 23112.4 Discussion 24612.5 Conclusion 25113 Smart Medication Dispensing: IoT Innovations in Drug Development 255Sapna Singh Kshatri, Mukesh Kumar Chandrakar, Devanand Bhonsle, Manjushree Nayak, Prashant Tamrakar and Pramisha Sharma13.1 Introduction 25613.2 Problem Identification 25813.3 Proposed Method 25913.4 Applications 26613.5 Use of ATMEGA328P Using Arduino 26813.6 Software Used 27213.7 Result and Discussion 27413.8 Conclusion 27514 Telemedicine and Virtual Health: Pioneering Innovation and Future Frontiers in Personalized Patient Care 279R. Rahul, R. Raghul Jayaprakash, M. Shibhi Varmaah and S. Velmurugan14.1 Introduction to Telemedicine and Virtual Health 28014.2 Challenges in Telemedicine 28314.3 Artificial Intelligence in Telemedicine 28914.4 Neurofeedback and Brain-Computer Interfaces (BCIs) in Telemedicine 29214.5 Blockchain Technology in Virtual Healthcare 29714.6 Telemedicine for Personalized Patient Care 30114.7 Future Directions of Telemedicine in Healthcare 30715 Blockchain Algorithm: Revolutionizing Healthcare Systems 313Ritika Awasthi and Arvind Tiwari15.1 Introduction 31415.2 How Blockchain can Relate to Healthcare 31515.3 Literature Review 31715.4 Features of Blockchain 32015.5 Blockchain Algorithms 32315.6 Network Model in Blockchain Algorithm 32915.7 Data Collection and Storage 33515.8 Diversity in Blockchain Technology 33715.9 Limitations of Blockchain 33915.10 Conclusion 34115.11 Future Work 34216 Enhancing Cyber-Physical System Security in Healthcare Through Ensemble Learning, Blockchain and Multi-Attribute Feature Selection 349Jagdish Pimple and Avinash Sharma16.1 Introduction 35016.2 Literature Survey 35516.3 Identification of the Problem 36216.4 Objectives 36316.5 Proposed Methodology 36416.6 Result and Discussion 36716.7 Conclusion and Future Work 37117 Digitizing Wellness: A Deep Dive Into EHR/EMR Systems 375Parul Dubey, Anansingh Thinakaran and Rajendra Motiramji Rewatkar17.1 Introduction 37617.2 Literature Review 37617.3 AWS and Healthcare Solutions 37817.4 AWS Services for Healthcare 37917.5 Building EHR/EMR Solutions on AWS 38117.6 Innovating with AI and Analytics 38317.7 Case Studies 38817.8 Proposed Architecture Overview 39017.9 Conclusion 39218 Harmony in Healthcare: Implementing an AI-Powered Biometric System 397S. Sharmila, M. Nirmala, Somasundaram Devaraj and M. Menagadevi18.1 Introduction to Biometric System 39818.2 Types of Biometric Systems 39818.3 Biometrics in Healthcare Application 40418.4 Biometric System for Monitoring and Disease Diagnosis 40918.5 Future Direction of Biometrics in Personalized Care 41519 Investigating the Revolution of Healthcare Application with Intense Comparisons and Case Study 421Amudhavalli P., S. Urmela, Vishnupriya G., N. Gopinath, R. Anandh and Lyndsay R. Buckingham19.1 Introduction 42219.2 Digital Twin 42419.3 Case Study--Healthcare Applications 43419.4 Future Research Ideas 44019.5 Conclusion 441References 442Index 447
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