This thesis explores the ethical implications of using facial recognition artificial intelligence (AI) technologies in medicine, with a focus on both the opportunities and challenges presented by the use of this technology in the diagnosis and treatment of rare genetic disorders. We highlight the positive outcomes of using AI in medicine, such as accuracy and efficiency in diagnosing rare genetic disorders, while also examining the ethical concerns including bias, misdiagnosis, the issues it may cause within patient-clinician relationships, misuses outside of medicine, and privacy. This paper draws on the opinions of medical providers and other professionals outside of medicine, which finds that while many are excited about the potential of AI to improve medicine, concerns remain about the ethical implications of these technologies. We discuss current legislation controlling the use of AI in healthcare and its ambiguity. Overall, this thesis highlights the need for further research and public discourse to address the ethical implications of using facial recognition and AI technologies in medicine, while also providing recommendations for its future use in medicine.

Our work explores a fascinating experiment in physics and science, the Double-Slit Experiment. We cover the mystery of this experiment, representing the wave and particle nature of photons, electrons, and quantum elements. We recount the history of quantum physics, an unknown field for most people due to its detachment from the world we see. Finally, we explore the capability of the human eye to detect light in its quantum state, closing the gap between us and quantum physics.

Our work explores a fascinating experiment in physics and science, the Double-Slit Experiment. We cover the mystery of this experiment, representing the wave and particle nature of photons, electrons, and quantum elements. We recount the history of quantum physics, an unknown field for most people due to its detachment from the world we see. Finally, we explore the capability of the human eye to detect light in its quantum state, closing the gap between us and quantum physics.

Computational and systems biology are rapidly growing fields of academic study, but unfamiliar researchers are impeded by a lack of accessible, programming-optional, modelling tools. To address this gap, I developed BioSSA, a web framework built on JavaScript and D3.js which allows users to explore a small library of curated biophysical models as well as create and simulate their own reaction network. The mathematical foundation of BioSSA is the Stochastic Gillespie Algorithm, which is widely used in mathematical modeling and biology to represent chemical reaction systems. SGA is particularly well-suited as an introductory modelling tool because of its flexibility, broad applicability, and its ability to numerically approximate systems when analytical solutions are not available. BioSSA is freely available to the community and further improvements are planned.