Artificial Intelligence and Machine Learning

图书简介

This book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used.Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances.With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

Chapter 1. Deep Learning Strategies in Biomedicine Imaging Technique P. Jayadharshini, Santhiya S, Keerthika S, and Priyanka S 2. X-Ray-Based Pneumonia Detection Using ResNet50 and VGG16 Extracted Features and Conventional Machine Learning Algorithms Amit Virmani, Akhilesh Singh, Ritesh Agarwal, Sanjeet Kumar, and Hemant Kumar 3. Enrichment of Human Life through Intelligent Wearable Technology Santhiya S, Jayadharshini P, Abinaya N, Sharmila C, Vasugi M, and Swetha Nallamangai K N 4. Reliability and Validity of Survey Questionnaires for Identifying Learning Disabilities in an Intelligent Tutoring System Neelu Jyothi Ahuja, Sarthika Dutt, and Swati Arya 5. A Survey of Artificial Intelligent Techniques for Cancer Detection Neha Nandal and Rohit Tanwar 6. Ethical Issues in Medical Data Naga Durga Saile K and B. Venkatesh 7. AI-Based Waste Classification in the Healthcare Industry Saswati Kumari Behera, Aouthithiye Barathwaj SR Y, Vasundhara L, Saisudha G, and Haariharan N C 8. SmartWear: An IoT-Based Integration of Home Automation and Healthcare Watch Saswati Kumari Behera, Saisudha G, and Vasundhara L 9. An Analytical Comparison of the Identification of Non-Small Cell Lung Cancer Nodules Using CT Scans and Prominent Deep Learning Models Sunil Kumar, Vishal Awasthi, Amar Pal Yadav, Shivneet Tripathi, and Prachi Chhabra 10. Abnormality Classifications Using Machine Learning Anupam Singh, Ravendra Singh, and Nitin Arora 11. Multilayer Perceptron-Based Speech Emotion Recognition for Identifying the Problematic Skills of Dyslexic Learners Sarthika Dutt, Rohit Kanauzia, Aditi, and Himanshu Bartwal 12. An Improved Convolutional Neural Network-Based Detection Framework for COVID-19 Omicron and Delta Variants Employing CT Sca

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Artificial Intelligence and Machine Learning（Innovations in Health Informatics and Healthcare） 人工智能与机器学习：新兴技术的智能展望 机械史

Artificial Intelligence and Machine Learning（Innovations in Health Informatics and Healthcare）

人工智能与机器学习：新兴技术的智能展望
机械史