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- All Subjects: artificial intelligence
- All Subjects: SARS-CoV-2
As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).
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.
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.
coronavirus 2 (SARS-CoV-2), has been responsible for significant social and economic
disruption, prompting an urgent search for therapeutic solutions. The spike protein of the virus
has been examined as an immunogenic target because of its role in viral binding and fusion
necessary for infection of host cells. Previous studies have identified a recombinant protein
(denoted as S1) that has been shown to potentially induce a neutralizing antibody response by
mimicking the structure of the SARS-CoV-2 spike protein. We have produced the S1 in plants
using agroinfiltration, a plant transformation technique whereby plasmid-containing
Agrobacterium tumefaciens is injected into Nicotiana benthamiana plants, resulting in transfer of
the desired gene from bacteria to plant cells. S1 was expressed to high levels within 5 days of
infiltration, and Western blot analysis showed recognition of the S1 by an anti-S1 antibody.
ELISA results exhibited increased binding activity to anti-S1 with increasing concentrations of
S1, indicating their specific interaction. This ongoing study will demonstrate the potential of a
plant-produced S1 as a vaccine, therapeutic, and diagnostic tool against COVID-19 that is not
only effective, but also cost-efficient and scalable in comparison to conventional mammalian cell
culture production methods.
An exploration into the history of the 1918 Influenza Pandemic and the societal impacts associated with it, as well as an analysis of the developing SARS-CoV-2 pandemic today. Based upon these analyses, similarities were drawn between the two pandemics which suggested a lack of innovation in preventative measures over the last century. Given this conclusion a series of proposals were made that should be further explored to give not only the United States, but the world at large, a better chance in the face of the next emerging disease.