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Full Description
The book emphasizes the role of data in driving healthcare transformation, providing readers with a roadmap for understanding and effectively implementing data-driven innovations. It delves into the applications of big data analytics, unveiling valuable insights and offering real-time decision support to healthcare professionals and goes on to review the role of machine learning and artificial intelligence in enabling accurate diagnosis, personalized treatment recommendations, and predictive modeling.
The book is an invaluable resource for healthcare professionals, researchers, policymakers, and technology enthusiasts alike. Its practical insights and perspectives empower stakeholders to leverage data-driven technologies effectively, thus fostering continuous improvements in patient care and shaping a brighter future for the healthcare industry as a whole.
Contents
Preface. Big Data's Impact on Healthcare Transformation. Artificial Intelligence and Machine Learning Approaches for Healthcare. Predictive Analytics Tools and Techniques for Disease Prevention and Early Detection in Healthcare Sector. Machine Learning-Based Analysis for Detection of Pancreatic Adenocarcinoma Using Urinary Biomarkers. Gland Segmentation in Colon Histology Images Using Deep Learning Method. Comparative Analysis for Detecting Cancer in Various Organs using Cellular Automata based Segmentation Technique. Convolutional Neural Networks and Transfer Learning for Medical Image Analysis: A Comprehensive Review. Multi-Objective Optimisation Enabled Improved Feature Selection. IoT-Blockchain in Remote Pregnancy Care Coordination. Strengthening Healthcare Data Security and Privacy. The Future of Healthcare: Data-driven Trends and Innovation. Index.
