Machine Learning in Islamic Medicine: An Ethical Approach to Precision Treatment and Health Equity

Abstract

Machine learning (ML) is transforming various sectors, and healthcare is one 
of the most promising domains benefiting from this technology. In Islamic medicine, 
the integration of ML offers the potential to revolutionize precision treatment, enabling 
healthcare professionals to offer highly individualized care based on patients' unique 
genetic, environmental, and lifestyle factors. However, the adoption of ML in 
healthcare also raises several ethical concerns, particularly regarding privacy, equity, 
and the influence of data-driven decisions on human well-being. Islamic ethical 
principles, rooted in justice, privacy, and the sanctity of life, offer a unique framework 
for addressing these challenges. This paper explores how Islamic medicine can guide 
the ethical implementation of ML technologies in healthcare systems, focusing on 
precision treatment and the promotion of health equity. By examining the concepts of 
Adela (justice), Ahsan (benevolence), and Taw hid (unity) in Islamic teachings, this 
research outlines a path for balancing technological advancement with ethical 
responsibility, ensuring that ML-driven healthcare services are accessible, fair, and 
morally sound. Furthermore, the paper discusses the potential of ML to reduce health 
disparities by identifying patterns that contribute to unequal access to healthcare, and 
the role of Islamic values in shaping more inclusive and equitable healthcare practices.