Artificial Intelligence in Biomedical and Modern Healthcare Informatics

Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of current trends in AI and machine learning within health care diagnosis. Its practical approach in healthcare gives insights into wearable sensors and device modules to help doctors and their patients in enhanced healthcare systems. The book helps readers detect common difficulties and their solutions for early detection and prediction of any disease. In 34 chapters, the book provides 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. Discusses fundamental and advanced approaches as well as optimization techniques used in AI for healthcare systemsIncludes chapters on various established imaging methods as well as emerging methods such as skin cancer, brain tumor, epileptic seizures, and kidney diseasesAdopts a bottom-up approach and proposes recent trends in simple manner with the help of real-world examplesSynthesizes the existing international evidence and expert opinion on implementing decommissioning in health care INDICE: 1. Recent Trends in Metabolomics and Artificial Intelligence2. Epilepsy Detection System using CWT and Deep-CNN3. Isolated Indian Sign Language Recognition with Multihead Attention Transformer based network and Mediapipe’s landmarks4. Electroencephalography (EEG) and Epilepsy5. A comprehensive review on state of art imagined speech decoding techniques using Electroencephalography6. Diagnosis of Parkinson’s Disease based on Biological and Imaging-derived features using Machine learning and Deep learning7. Impact of Artificial Intelligence On Public Health: A Prospective Study On Medical Social Work Practice8. Upshots of Healthcare with AI9. Parkinson's Disease Diagnosis, Treatment, and Future Scope: An Epilogue10. Brain Tumor and Feature Detection from MRI and CT scan using Artificial Intelligence11. Neuromodulation via Brain Stimulation: A Promising Therapeutic Perspective for Alzheimer’s Disease12. A Biosensor for the Detection of Viruses using One-Dimensional Photonic Crystals13. Artificial Intelligence Based Seizure Detection Systems in Electroencephalography: Transforming Healthcare for Accurate Diagnosis and Treatment14. Artificial Intelligence and Image Enhancement based methodologies used for detection of tumor in MRIs of human brain15. Machine learning based workload Identification using Functional Near-Infrared Spectroscopy (fNIRS) Data16. Forecasting the COVID-19 pandemic through the hybridization of Machine Intelligent Algorithms17. Suppression of Noise Signals from Computed Tomography and Ultrasound Medical Images and Performance Evaluation18. Recent Advances in Removal of Artefacts from EEG Signal Records19. Prediction of Non-Alcoholic Fat Liver Disease Using Machine Learning20. Evaluation of Diabetes Classification with Machine Learning Framework21. Various Segmentation Methods/ Techniques for Medical Images and The Role of IoT22. A Review on Brain Computer Interface and its Applications23. Augmented Mass Detection of Breast Cancer in Mammogram Images Using Deep Intelligent Neural Network Model24. CNC Machines in Production of Medical Devices25. Artificial Intelligence and Machine Learning Assisted Robotic Surgery: Current Trends and Future Scope26. Computer Aided Diagnosis in Health Care: Case Study on Lung Cancer Diagnosis27. Artificial Intelligence in respiratory diseases with special insight through bioinformatics28. Analysis and prediction of Cardiomyopathy using Artificial Intelligence29. A Preemptive Approach to Polycystic Ovary Syndrome Diagnosis using Machine Learning30. AI and its role in predictive preclinical models for drug efficacy testing31. Mapping the Landscape of Human Activity Recognition Techniques in Health Monitoring for Chronic Disease Management32. Analysis and Organization of Mycological Skin Contaminations by Means of Medicinal Imagery33. A Sensitive Biosensor for the Detection of Blood Components Using 2D Photonic Crystals34. Machine Learning Assisted EEG Signal Classification for Automated Diagnosis of Mental Stress35. A Deep Perspective of Blockchain Applications in Healthcare Sector and Industry 4.036. Analyzing the role of Machine Learning Techniques in Healthcare Systems37. CNN based Deep Learning model for Skin Cancer detection using Dermatoscopic Images38. Bioelectrical Impedance Analysis Body Composition Estimation of Fat Mass Percentage in People with Spinal Cord Injury39. Advanced EEG Signal Processing and Feature Extraction Concepts40. Fractal Analysis on Biomedical Signal41. Detection of Metastasis Osteosarcoma Using Deep Fuzzy Gradient Recurrent Convolutional Neural Network42. Deep Learning Based Fatigue Detection Using Functional Connectivity43. Brain Tumor Diagnosis Using Image Classifier44. Machine Learning-based Solutions for Brain Tumor Detection: Comparative Study and Limitations45. ISL Recognition System in Realtime using TensorFlow API46. Indoor and Home-Based Post-Stroke Rehabilitation Techniques- A Systemic Review47. Exploring the Exciting Potential and Challenges of Brain-Computer Interfaces (BCI) 48. Transmission Dynamics of COVID-19 Virus Disease49. Design of High Voltage Biphasic Pulse Generation Circuit with 3-Level Isolation Suitable for AED Applications50. A Novel Scheme of Brain Tumor Detection from MRIs using K-Means Segmentation and Histogram Analysis51. Analyzing Post COVID-19 Effects on Self-Consciousness and Awareness towards Health: A Neuroscience Framework52. Crowdsourcing and Artificial Intelligence based Modeling Framework for effective Public Healthcare Informatics and Smart eHealth System53. Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) in Biomedical Fields: A Prospect in Improvising Medical Healthcare Systems54. A comprehensive study on implementable antennas for medical applications55. Deep Learning for Bone Age Assessment: Current Status and Future Prospects56. Emerging Applications of Artificial Intelligence in Analyzing EEG Signals for the Healthcare Sector

• ISBN: 978-0-443-21870-5
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 316
• Fecha Publicación: 01/09/2024
• Nº Volúmenes: 1
• Idioma: Inglés