M. A. Ansari – författare

Computational Intelligence in Healthcare Applications discusses a variety of techniques designed to represent, enhance and empower inter-domain research based on computational intelligence in healthcare. The book serves as a reference for the pervasive healthcare domain which takes into consideration new convergent computing and other applications. The book discusses topics such as mathematical modeling in medical imaging, predictive modeling based on artificial intelligence and deep learning, smart healthcare and wearable devices, and evidence-based predictive modeling. In addition, it discusses computer-aided diagnostic for clinical inferences and pervasive and ubiquitous techniques in healthcare.

This book is a valuable resource for graduate students and researchers in medical informatics, however, it is also ideal for members of the biomedical field and healthcare industry who are interested in learning more about novel technologies and their applications in the field.

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.