Early-Stage Detection for Alzheimer Disease Using Machine Learning and Deep Learning Algorithm: A Research-Oriented Approach to Intelligent Medical Diagnosis

Alzheimer’s disease is one of the most challenging neurodegenerative disorders affecting millions of people worldwide. Early and accurate diagnosis plays a critical role in improving treatment planning and patient care. This book explores the application of Machine Learning and Deep Learning algorithms for the early-stage detection of Alzheimer’s disease using medical imaging and healthcare data. The book presents research-oriented methodologies, predictive models, data preprocessing techniques, feature extraction methods, and performance evaluation metrics used in intelligent disease detection systems. It also highlights the role of Convolutional Neural Networks (CNNs), classification algorithms, and AI-driven healthcare analytics in enhancing diagnostic accuracy. Designed for students, researchers, and healthcare technology enthusiasts, this book provides valuable insights into the intersection of Artificial Intelligence and medical science while demonstrating how modern computational techniques can support early diagnosis and improve healthcare outcomes.