Dr. Sheun Aluko, MD, currently serves as an Instructor in Medicine for the Division of Hospital Medicine. Dr. Aluko completed a degree in biomedical engineering at Washington University and then completed medical school at Stanford University School of Medicine. He continued to hone his engineering skills by completing a master’s in biomedical informatics while at Stanford, with the goal of fusing his medical and computer science knowledge to develop innovative healthcare software solutions for patients and providers. Dr. Aluko then completed a medicine residency at Washington University in St. Louis/Barnes Jewish Hospital, after which he continued as an instructor of medicine. His expertise spans managing chronic illnesses, addressing multisystem disease conditions, and promoting health and wellness to prevent disease. Dr. Aluko’s practice is rooted in a thorough understanding of internal medicine’s broad scope, from primary care to the intricacies of various subspecialties.
Education
- B.S., Biomedical Engineering: Washington University, St. Louis, MO (2015)
- M.D.: Stanford University School of Medicine, Stanford, CA (2021)
- M.S., Biomedical Informatics: Stanford University School of Medicine, Stanford, CA (2021)
Research
Medik: A Modern Educational Diagnostic Tool (2020)
Led a team in creating a medical, educational tool which performs automated diagnosis given a list of symptoms, by querying Google Data Commons, an open access knowledge base [https://medikapp-274018.web.app/]
Liver Lesion Localization using Deep Convolutional Neural Networks, CS230 (2019) Explored the application of custom neural networks and the Faster RCNN network to the task of liver lesion localization using the NIH Deep Lesion Dataset.
Stanford University Habtezion Lab, Department of Gastroenterology and Hepatology (2019)
Independently Developed a Web Application to display human blood immuno-analyte data collected as part of our research study, “Effects of processing conditions on stability of immune analytes in human blood”. The paper was published in Nature Scientific Reports and the web application is live at the following link: [https://immuno19.web.app/]
Publications
Gottfried-Blackmore, A., Rubin, S.J.S., Bai, L. et al. Effects of processing conditions on stability of immune analytes in human blood. Sci Rep 10, 17328 (2020). https://doi.org/10.1038/s41598-020-74274-8
Presentations
Design and Implementation of an Immuno-analyte Data Visualization Website As part of the Biomedical Informatics Departmental Talk Series at Stanford, I outlined the design and implementation of the web application developed for the research study mentioned above, “Effects of processing conditions on stability of immune analytes in human blood.” I covered considerations such as choice of cloud platform, backend database, web development framework, data visualization library, and prototyping environment. (2020)