This book examines computer vision and IoT-integrated technologies used by medical professionals in decision-making, for sustainable development in a healthcare ecosystem and to better serve patients and stakeholders. It discusses machine vision, AI-driven computer vision, machine learning, deep learning, and AI-integrated IoT technologies.
This book examines computer vision and IoT-integrated technologies used by medical professionals in decision-making, for sustainable development in a healthcare ecosystem, and to better serve patients and stakeholders. It looks at the methodologies, technologies, models, frameworks, and practices necessary to resolve the challenging issues associated with leveraging the emerging technologies driving the medical field.
Chapters discuss machine vision, AI-driven computer vision, machine learning, deep learning, AI-integrated IoT technology, data science, blockchain, AR/VR technology, cloud data, and cybersecurity techniques in designing and implementing a smart healthcare infrastructure in the era of the Industrial Revolution 4.0. Techniques are applied to the detection, diagnosis, and monitoring of a wide range of health issues.
Computer Vision and AI-integrated IoT Technologies in the Medical Ecosystem targets a mixed audience of students, engineers, researchers, academics, and professionals who are researching and working in the field of medical and healthcare industries from different environments and countries.
1 Application of Computer Vision (CV) in the Healthcare Ecosystem 2
Artificial Intelligence (AI)-Assisted Computer Vision (CV) in Healthcare
Systems 3 Computer Vision (CV)-based Machine Learning (ML) Models for
Healthcare System 4 Computer Vision (CV)-Aided Medical Diagnosis for
Cardiovascular Disease Detection 5 Artificial Intelligence (AI)-Aided
Diagnosis System to Objectively Measure Chronic Pain 6 Artificial
Intelligence (AI)-Enabled Technology in Medicine-Advancing Holistic
Healthcare Monitoring and Control Systems 7 Medical and Biomedical Signal
Processing and Prediction Using EEG Machine and Electroencephalography 8
Artificial Intelligence (AI)-Aided Computer Vision (CV) in Healthcare System
9 Artificial Intelligence (AI) Models for Disease Diagnosis and Prediction of
Heart Disease with Artificial Neural Networks (ANN) 10 Harnessing Deep
Learning (DL) for Image Inpainting in Healthcare System-Methods and
Challenges 11 Skin Cancer Classification Using ConvNeXtLarge Architecture 12
Brain Tumor Detection Using Tensorflow Framework 13 Early Prediction of
Sepsis with the Predictive Analysis Model Using 1.5 Million Records 14 An
Efficient FPGA Implementation of Approximate Multiply Accumulate Unit for
Image and Video Processing Applications in Healthcare Sector 15 Lung Cancer
Prediction Using Convolutional Neural Network (CNN) with VGG16 Model 16
Identifying Error and Bias in Chest Radiographic Images for COVID Detection
Using Deep Learning Algorithms 17 Forecast of Health Risk for Chronic Kidney
Disease: A Comparison between Naïve Bayes (NB) and Support Vector Machine
(SVM) Models 18 The Performance of Feature Selection Approaches on Boosted
Random Forests Algorithm for Predicting Cardiovascular Disease 19 Application
of Artificial intelligence (AI) Technologies in Employing Chatbots to Access
Mental Health 20 Clinical Decision Support Systems in Smart Medical Ecosystem
21 The Future of Edge Computing for Healthcare Ecosystem 22 Privacy-Aware
IoT-Based Multi-Disease Diagnosis Model for Healthcare System 23 Using Big
Data to Solve Problems in the Field of Medicine 24 Automations and Robotics
Improves Quality Healthcare in the Era of Digital Medical Laboratory
Alex Khang is a professor of Information Technology, AI and data scientist, software industry expert, and the Chief of Technology Officer (AI and Data Science Research Center) at the Global Research Institute of Technology and Engineering, North Carolina, United States.
Vugar Abdullayev, Doctor of Technical Sciences, is an associate professor in the Computer Engineering Department at the Azerbaijan State Oil and Industry University, Baku, Azerbaijan.
Olena Hrybiuk, Doctor of Pedagogical Sciences, is an associate professor and researcher at the Faculty of Engineering, International Science and Technology University, National Academy of Sciences, Ukraine.
Arvind K. Shukla is a professor and head of department at the Department of Computer Applications, IFTM University, Moradabad, India.
