The prevalence of chronic diseases, particularly heart and liver disorders, remains a critical public health concern worldwide. Early identification of individuals at risk can significantly enhance preventive healthcare measures. This paper explores the application of an automated system to assess susceptibility to heart and liver diseases in married individuals. By integrating medical history, lifestyle patterns, genetic predispositions, and biometric data, the system provides a predictive analysis using machine learning algorithms. The study emphasizes the importance of personalized health risk assessment, especially in the context of marital health screening and long-term family planning. Results demonstrate the system's potential in offering timely insights and enabling healthcare professionals to design tailored preventive interventions.

Heart diseases, liver diseases, automated system, susceptibility, health screening, married individuals, predictive healthcare, artificial intelligence, preventive medicine.

World Health Organization. (2023). Cardiovascular diseases (CVDs).

European Association for the Study of the Liver (EASL). (2022). Clinical Practice Guidelines on the management of liver disease.

Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.

Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine Learning in Medicine. New England Journal of Medicine, 380(14), 1347–1358.