Translational Epidemiology, ScB
Advisor: Indra Neil Sarkar
Thesis: Prediction of bacterial STIs among MSM in Rhode Island: A machine learning approach
Thesis Advisor: Indra Neil Sarkar, Philip Chan, Brandon Marshall
Translational Epidemiology combines two reciprocal fields of inquiry in health and disease: population health and bioinformatics. Through quantitative investigation of both the biological and socio-behavioral components of disease, this concentration aims to better understand how individual-level factors impact the health of communities.
I utilized patient clinical and demographic information, collected at a publicly-funded STD clinic in Rhode Island, to design a clinical decision support system to estimate the risk of an individual testing positive for a bacterial STI. This system can be used to assist clinicians optimally prescribe antibiotic treatment to reduce the asymptomatic spread of bacterial STIs and reduce selective pressure for resistance mutations.
Acknowledgments: Many thanks to my family, friends, and mentors/thesis committee.
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"It was such a pleasure to work with you, Will! Congratulations on completing your degree and I wish you all the best!" --Neil Sarkar
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