AI Models for Analyzing Health Related Concepts in the Qur'an

This book is a structured examination of how computational intelligence can be employed to interpret and correlate health-related themes across sacred scripture and modern biomedical literature. The book outlines the design of machine learning architectures, including transformer-based language models and semantic knowledge graphs, to extract, classify, and compare concepts such as nutrition, hygiene, preventive care, and psychological well-being. It emphasizes methodological rigor in aligning theological discourse with evidence-based medical frameworks, addressing issues of contextual hermeneutics, linguistic variance, and data validation. Through interdisciplinary integration, the work proposes analytical pipelines that enable scalable text mining while maintaining scholarly sensitivity. The result is a model-driven approach to identifying convergences and divergences between spiritual guidance and contemporary health science.