Disruptive Developments in Biomedical Applications

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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.

    Author(s): Swati V. Shinde, Parikshit N. Mahalle, Varsha Bendre, Oscar Castillo
    Publisher: CRC Press
    Year: 2022

    Language: English
    Pages: 358
    City: Boca Raton

    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