Geographic Information Systems for Medical Data Analysis

Geographic Information Systems (GIS) have transformed how health-related information is understood and managed. By integrating spatial data with medical, epidemiological, and environmental datasets, GIS enables researchers and healthcare professionals to identify patterns, visualize disease spread, assess access to care, and examine the influence of social and environmental determinants on health outcomes. The combination of GIS with advanced analytical techniques, including machine learning and predictive modeling, further strengthens data-driven decision-making in public health, clinical practice, and policy development. Despite this potential, GIS remains underutilized in many healthcare research contexts, making a more systematic exploration of its applications both timely and essential. Geographic Information Systems for Medical Data Analysis provides a comprehensive overview of GIS principles and tools as applied to medical and health data. By integrating theoretical frameworks, methodological guidance, and practical applications, this book advances the field of geospatial health analytics and demonstrates how GIS can inform public health interventions, resource allocation, and policy decision-making. Covering topics such as hotspot forecasting, explainable risk surfaces, and disease risk prediction, this book is a fundamental academic resource for graduate and doctoral students, healthcare professionals, data scientists, GIS practitioners, and more.