A Proposed System of Smart Diagnosis based on AI for Early Disease Detection Aligned with Islamic Healthcare Values

Abstract

The rapid advancement of machine learning and web technologies is transforming the healthcare sector, offering innovative solutions for disease diagnosis and management. This conceptual paper explores the development of a web-based disease detection platform that utilizes machine learning algorithms to predict potential diseases based on user-reported symptoms. The primary objective of this platform is to provide users with accurate diagnostic results, enhancing the accessibility and efficiency of healthcare services. A distinctive feature of this platform is its integration of Islamic principles, specifically the inclusion of INAQ (Islamic Network for Artificial Intelligence) elements, such as the practice of Ruqyah (spiritual healing), within the technological framework. This approach seeks to align the proposed platform with the Islamic understanding of Tawhid (the Oneness of God) and its relationship to knowledge and healing. The proposed platform will design with a user-friendly interface to ensure accessibility for individuals with varying levels of technological literacy. It aims to bridge the gap between modern medical technologies and traditional Islamic perspectives on health and healing, offering a culturally sensitive solution to healthcare challenges. By embedding Islamic ethical considerations, the platform provides a holistic approach to disease detection, which acknowledges both the scientific and spiritual dimensions of health. This work contributes to the emerging field of culturally inclusive healthcare solutions, laying the groundwork for future research and development in medical technologies that respect and incorporate diverse cultural and religious values. The proposed platform highlights the potential for AI-driven healthcare innovations that are both technically advanced and socially sensitive, thus setting the stage for inclusive, ethically grounded solutions in healthcare technology.

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