Название: Modern Technologies in Healthcare
Автор: Temitope Emmanuel Komolafe, Patrice Monkam, Blessing Funmi Komolafe, Nizhuan Wang
Издательство: CRC Press
Серия: Analytics and AI for Healthcare
Год: 2025
Страниц: 348
Язык: английский
Формат: pdf (true), epub
Размер: 16.8 MB

This book comprehensively explores the latest technological advancements in healthcare, with a particular focus on the application of cutting-edge technologies, such as Artificial Intelligence (AI), Computer Vision, and robotics. The focus extends across crucial domains, such as disease diagnosis and monitoring, medical imaging, and the facilitation of remote healthcare services.

The book provides a comprehensive overview of AI techniques for intelligent diagnoses, discussing how Machine Learning and Deep Learning models enhance accuracy and speed in medical imaging, diagnostics, and patient care. It also delves into the integration of AI with other disciplines, such as Data Science, computer vision, edge computing, robotics, and web development, to tackle complex medical challenges. Moreover, it highlights current trends and future prospects in surgery, rehabilitation, neuroscience, and automated healthcare systems, offering valuable insights into the future of technology-driven healthcare solutions. The chapters are authored by researchers and professionals from every region of the globe, including Africa, Asia, the Americas, Europe, and Oceania. This global contribution highlights the versatility and broad perspectives of the shared insights and conclusions presented in the book.

The core of intelligent medical image classification is to use Machine Learning and Deep Learning algorithms to extract features from medical image data and classify them. Traditional Machine Learning methods include support vector machines (SVM), decision trees, random forests, etc., while Deep Learning methods have attracted much attention for their excellent performance in image recognition and classification tasks, especially the application of CNN. By training on a large number of medical image data, the intelligent classification system can learn the feature representation in the image and achieve accurate classification and recognition of different diseases and lesions.

This book is an essential guide for healthcare professionals, researchers, and enthusiasts eager to understand and actively contribute to shaping the future of healthcare through the integration of AI and other disciplines.