Prognostic Models in Healthcare: AI and Statistical Approaches

This book focuses on contemporary technologies and research in computational intelligence that have reached the practical level and are now accessible in preclinical and clinical settings. It emphasizes the use of machine learning and deep learning to automate diagnosis and prognosis, and the importance of big data analytics in healthcare. It contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms.

Format: Hardback
Length: 504 pages
Publication date: 07 July 2022
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the forefront of contemporary technologies and cutting-edge research in computational intelligence, showcasing its practical applications in preclinical and clinical settings. Its primary goal is to provide a deep understanding of significant technological advancements and groundbreaking research outcomes in predictive modeling within healthcare imaging and data analysis. By leveraging machine learning and deep learning techniques, the book aims to fully automate the diagnosis and prognosis of patients across various medical fields.

The healthcare industry has undergone a remarkable transformation, shifting its focus from a clinical-centric approach to a patient-centric model. However, despite these advancements, the industry continues to face numerous technical, computational, and ethical challenges.

In the realm of big data analytics, healthcare is experiencing a revolutionary shift, both in terms of technical capabilities and societal well-being perspectives. With the availability of vast amounts of regularly gathered data from the healthcare sector, the demand for predictive models and automated solutions for the early identification of critical and chronic illnesses has grown exponentially.

This book serves as an invaluable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers working in the healthcare industry. It encompasses high-quality, original work that offers readers a comprehensive exploration of novel applications and contexts for deep learning architectures and algorithms. By presenting a wealth of knowledge and insights, the book empowers readers to unlock the full potential of these technologies and drive meaningful advancements in healthcare.

Weight: 951g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811920561
Edition number: 1st ed. 2022