Full Description
Decision Support System for Diabetes Healthcare: Advancements and Applications is a comprehensive guide to the cutting-edge technology transforming diabetes management. In this book, leading experts in the field explore how decision support systems (DSS) are revolutionizing healthcare practices, particularly in diabetes care. From advanced data analytics to personalized treatment recommendations, this book delves into the innovative solutions that are reshaping how healthcare providers approach diabetes management. Readers will gain insights into the latest developments in DSS technology, including predictive modeling, machine learning algorithms, and real-time monitoring systems, all designed to enhance patient outcomes and improve quality of life.
With a focus on practical applications, Decision Support System for Diabetes Healthcare offers case studies and examples of successful DSS implementations across various healthcare settings. Whether you're a healthcare professional, researcher, or technology enthusiast, this book provides invaluable insights into the future of diabetes care. By exploring the intersection of technology and healthcare, readers will discover how DSS is empowering both patients and providers to make informed decisions, optimize treatment plans, and ultimately, transform the way diabetes is managed on a global scale.
Contents
1. Importance of Analyzing Causality for Diabetes Care. 2. Advances and Opportunities in Digital Diabetic Health Care Systems. 3. Role of IoT and Expert Systems in Diabetes Control with Continuous Diagnosis of Medical Conditions. 4. Harnessing Machine Intelligence and Big Data for Diabetes Management. 5. Machine Intelligence and Big Data in Diabetic Care: Laboratorian's Perspective. 6. EfficientNetB3-DTL: Classification of Diabetic Retinopathy Images using Modified EfficientNetB3 with Deep Transfer Learning. 7. Prediction and Diagnosis of Glaucoma in Fundus Images through Optic Cup and Optic Disk Segmentation. 8. Early Diagnosis of Diabetes using an Intelligent Machine Learning Technique. 9. Advanced Diabetes Prediction: A Comprehensive Analysis of Machine Learning and Deep Learning Techniques. 10. Intelligent Diagnosis Support System for Screening Diabetes Subjects using Hybrid Machine Learning Algorithms. 11. Cyber-Physical System for Managing Diabetic Health Care.
