THESIS
2023
1 online resource (xiii, 175 pages) : illustrations (chiefly color)
Abstract
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...[
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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.
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