Disruptive Developments in Biomedical Applications

This book covers advancements and future challenges in biomedical application development using disruptive technologies like AI, IoT and signal processing. 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, osteoarthritis, and so forth. 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 electronics health records (EHRs). Presents state of art research in the field of biomedical engineering using various physiological signals. Explores different Bio Sensors used in Healthcare Applications using IOT. This book aims at Graduate students and researchers in artificial intelligence, medical imaging, biomedical engineering, and internet of things. Cover Half Title Title Copyright Contents Editor Biographies List of Contributors Preface Part I AI/ML for Biomedical Applications Chapter 1 Recent Advances of Artificial Intelligence (AI) for Nanobiomedical Applications: Trends, Challenges, and Future Prospects Chapter 2 Medical Imaging Modalities and Different Image Processing Techniques: State of the Art Review Chapter 3 Prognosis and Diagnosis of Disease Using AI/ML Techniques Chapter 4 AI-Based Approach for Brain Tumor Detection and Classification Chapter 5 Prediction and Classification of Alzheimer’s Disease Using Machine Learning Models Chapter 6 Classification of Histopathology Images of Lung Cancer Using Convolutional Neural Network (CNN) Chapter 7 Case Study on Oropharyngeal Cancer Prediction and Diagnosis and Management Based Upon MRI, CT Scan Imaging Techniques Part II IOT and Smart Healthcare Chapter 8 Introduction to Smart Healthcare Using IoMT Chapter 9 A Webcam-Based Belt-System for Respiratory and Chest-Expansion Measurements Chapter 10 Novel Data Analysis Framework in Smart City Healthcare Part III Bio-Signal Processing Chapter 11 Evolution of Automatic Epilepsy Detection and Classification Techniques: A Survey Chapter 12 Evaluation of Boosting Algorithms for P300 Detection in EEG Signals Chapter 13 Comprehensive Study of Brain–Computer Interface (BCI) with Emphasis on Strategies Used for Processing the Signals Chapter 14 Fetal Electrocardiogram Extraction Using Adaptive Filters Approach Chapter 15 Detection of Heart Functioning Abnormalities (Arrhythmia) Using ECG Signals: A Systematic Review Chapter 16 Heart Rate Variability Analysis in Healthy Male Subjects with Comprehensive Age Groups Part IV Electronic Health Records Chapter 17 Electronic Health Records: Need, Challenges, and Future Scope Chapter 18 Role of EHR in Cancer Detection: Need, Challenges, and Future Scope of EHR Part V Recent Devlopement in Biomedical Applications Chapter 19 Implantable Pacemaker Low Power Telemetry Unit Chapter 20 Recent Advances in Drug Delivery Systems: MEMS Perspective Chapter 21 Estimating the Blood-Vessel Response to Vaso-Active Agents by Microscope Video Image Processing Chapter 22 Organ Donation and Transplantation Challenges, Opportunities, and the Role of Blockchain Index 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 covers advancements and future challenges in biomedical application development using disruptive technologies like AI, IoT and Signal Processing. Book is divided into 4 main sections namely medical image processing using AI, IoT and biomedical devices, signal processing and electronic health records, and advances with case studies.