This MPhil thesis explores the development of CuraBox. This intelligent health supplement recommendation system leverages machine learning techniques to deliver personalized dietary guidance tailored to individual health needs and preferences. In response to the escalating growth of the dietary supplement market and the concomitant challenge for consumers to navigate through the immense array of options, CuraBox offers a streamlined, data-driven approach to supplement selection.

CuraBox operates on a robust foundation of machine learning, nutrition research, personalized nutrition strategies, and big data in healthcare, combined with insights from e-commerce recommendation systems. It employs these techniques to process data from various sources, including user-reported information and...[ Read more ]

This MPhil thesis explores the development of CuraBox. This intelligent health supplement recommendation system leverages machine learning techniques to deliver personalized dietary guidance tailored to individual health needs and preferences. In response to the escalating growth of the dietary supplement market and the concomitant challenge for consumers to navigate through the immense array of options, CuraBox offers a streamlined, data-driven approach to supplement selection.

CuraBox operates on a robust foundation of machine learning, nutrition research, personalized nutrition strategies, and big data in healthcare, combined with insights from e-commerce recommendation systems. It employs these techniques to process data from various sources, including user-reported information and inputs from pharmaceutical professionals. The result is a platform capable of generating nuanced, personalized supplement recommendations that evolve as the system learns from incoming data.

This thesis outlines the rigorous testing process conducted with a sample of individuals to validate the effectiveness of CuraBox. It discusses using performance metrics such as recommendation accuracy and user satisfaction to gauge the system's effectiveness. CuraBox's potential to transform the supplement industry is emphasized, demonstrating its capacity to deliver personalized, evidence-based recommendations, thereby reducing the complexity of choices and enhancing health outcomes for consumers.

The entrepreneurial journey of developing CuraBox, including business plan formulation, technical product design, the application of machine learning, and entrepreneurship activities, is also detailed in this thesis. It further delves into the lessons learned from the process and the personal reflections gathered from the adventure of building a pioneering solution in the health and wellness industry.

The thesis culminates in a reflection on the achievements of CuraBox and a discussion on the future potential of advanced AI models in healthcare, laying the foundation for further developments and applications in this exciting intersection of technology and healthcare.