Swati V. Shinde – författare

This book covers advancements and future challenges in biomedical application development using disruptive technologies like artificial intelligence (AI), the Internet of Things (IoT), and signal processing. The book is divided into four main sections, namely, medical image processing using AI; IoT and biomedical devices; biomedical signal processing; and electronic health records, including advances in biomedical systems. It includes different case studies of biomedical applications using different AI algorithms related to diabetes, skin cancer, breast cancer, cervical cancer, and osteoarthritis.Features: Covers different technologies like AI, IoT, and signal processing in the context of biomedical applications. Reviews medical image analysis, disease detection, and prediction. Comprehends the advantage of recent technologies for medical record keeping through electronic health records (EHRs). Presents state-of-the-art research in the field of biomedical engineering using various physiological signals. Explores different bio sensors used in healthcare applications using IOT.This book is aimed at graduate students and researchers in AI, medical imaging, biomedical engineering, and IoT.

This book covers advancements and future challenges in biomedical application development using disruptive technologies like artificial intelligence (AI), the Internet of Things (IoT), and signal processing. The book is divided into four main sections, namely, medical image processing using AI; IoT and biomedical devices; biomedical signal processing; and electronic health records, including advances in biomedical systems. It includes different case studies of biomedical applications using different AI algorithms related to diabetes, skin cancer, breast cancer, cervical cancer, and osteoarthritis.Features: Covers different technologies like AI, IoT, and signal processing in the context of biomedical applications. Reviews medical image analysis, disease detection, and prediction. Comprehends the advantage of recent technologies for medical record keeping through electronic health records (EHRs). Presents state-of-the-art research in the field of biomedical engineering using various physiological signals. Explores different bio sensors used in healthcare applications using IOT.This book is aimed at graduate students and researchers in AI, medical imaging, biomedical engineering, and IoT.

This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems.Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images.The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.

This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems.Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images.The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments.Features:Covers a variety of deep learning architectures useful for computer vision tasksDemonstrates the use of different soft computing techniques and their applications for different computer vision tasksHighlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problemAddresses the different issues and further research opportunities in computer vision and soft computingDescribes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domainConsiders recent real word problems and the prospective solutions to these problemsThis book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.