Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system. The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease. The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications. With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare.

Table of Contents:
1. Impact of Artificial Intelligence on Public Health: A Prospective Study on Medical Social Work Practice 2. Upshots of Healthcare with AI 3. Artificial Intelligence and Machine Learning Assisted Robotic Surgery: Current Trends and Future Scope 4. A Deep Perspective of Blockchain Applications in Healthcare Sector and Industry 4.0 5. Analyzing the role of Machine Learning Techniques in Healthcare Systems 6. Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) in Biomedical Fields: A Prospect in Improvising Medical Healthcare Systems 7. Artificial Intelligence in respiratory diseases with special insight through bioinformatics 8. Electroencephalography (EEG) and Epilepsy 9. A Review on Brain Computer Interface and its Applications 10. Recent Trends in Metabolomics and Artificial Intelligence 11. A comprehensive review on state of art imagined speech decoding techniques using Electroencephalography 12. Parkinson's Disease Diagnosis, Treatment, and Future Scope: An Epilogue 13. Recent Advances in Removal of Artefacts from EEG Signal Records 14. Computer Aided Diagnosis in Health Care: Case Study on Lung Cancer Diagnosis 15. AI and its role in predictive preclinical models for drug efficacy testing 16. Machine Learning-based Solutions for Brain Tumor Detection: Comparative Study and Limitations 17. Indoor and Home-Based Post-Stroke Rehabilitation Techniques- A Systemic Review 18. A comprehensive study on implementable antennas for medical applications 19. Deep Learning for Bone Age Assessment: Current Status and Future Prospects 20. Emerging Applications of Artificial Intelligence in Analyzing EEG Signals for the Healthcare Sector 21. Epilepsy Detection System using CWT and Deep-CNN 22. Isolated Indian Sign Language Recognition with Multihead Attention Transformer based network and Mediapipe’s landmarks 23. Diagnosis of Parkinson’s Disease based on Biological and Imaging-derived features using Machine learning and Deep learning 24. Brain Tumor and Feature Detection from MRI and CT scan using Artificial Intelligence 25. Neuromodulation via Brain Stimulation: A Promising Therapeutic Perspective for Alzheimer’s Disease 26. A Biosensor for the Detection of Viruses using One-Dimensional Photonic Crystals 27. Artificial Intelligence Based Seizure Detection Systems in Electroencephalography: Transforming Healthcare for Accurate Diagnosis and Treatment 28. Artificial Intelligence and Image Enhancement based methodologies used for detection of tumor in MRIs of human brain 29. Machine learning based workload Identification using Functional Near-Infrared Spectroscopy (fNIRS) Data 30. Forecasting the COVID-19 pandemic through the hybridization of Machine Intelligent Algorithms 31. Suppression of Noise Signals from Computed Tomography and Ultrasound Medical Images and Performance Evaluation 32. Prediction Of Non-Alcoholic Fat Liver Disease Using Machine Learning 33. Evaluation of Diabetes Classification with Machine Learning Framework 34. Various Segmentation Methods/ Techniques for Medical Images and The Role of IoT 35. Augmented Mass Detection of Breast Cancer in Mammogram Images Using Deep Intelligent Neural Network Model 36. CNC Machines in Production of Medical Devices 37. Analysis and prediction of Cardiomyopathy using Artificial Intelligence 38. A Preemptive Approach to Polycystic Ovary Syndrome Diagnosis using Machine Learning 39. Mapping the Landscape of Human Activity Recognition Techniques in Health Monitoring for Chronic Disease Management 40. Analysis and Organization of Mycological Skin Contaminations by Means of Medicinal Imagery 41. A Sensitive Biosensor for the Detection of Blood Components Using 2D Photonic Crystals 42. Machine Learning Assisted EEG Signal Classification for Automated Diagnosis of Mental Stress 43. CNN based Deep Learning model for Skin Cancer detection using Dermatoscopic Images 44. Bioelectrical Impedance Analysis Body Composition Estimation of Fat Mass Percentage in People with Spinal Cord Injury 45. Advanced EEG Signal Processing and Feature Extraction Concepts 46. Fractal Analysis on Biomedical Signal 47. Detection of Metastasis Osteosarcoma Using Deep Fuzzy Gradient Recurrent Convolutional Neural Network 48. Deep Learning Based Fatigue Detection Using Functional Connectivity 49. Brain Tumor Diagnosis Using Image Classifier 50. ISL Recognition System in Realtime using TensorFlow API 51. Exploring the Exciting Potential and Challenges of Brain-Computer Interfaces (BCI) 52. Transmission Dynamics of COVID-19 Virus Disease 53. Design of High Voltage Biphasic Pulse Generation Circuit with 3-Level Isolation Suitable for AED Applications 54. A Novel Scheme of Brain Tumor Detection from MRIs using K-Means Segmentation and Histogram Analysis 55. Analyzing Post COVID-19 Effects on Self-Consciousness and Awareness towards Health: A Neuroscience Framework 56. Crowdsourcing and Artificial Intelligence based Modeling Framework for effective Public Healthcare Informatics and Smart eHealth System