Harvard Medical School | United States
Ms. Siona Prasad is a dedicated medical researcher and md candidate at harvard medical school, boston, massachusetts, pursuing her degree through the pathways program with an expected graduation. She graduated summa cum laude from harvard university with an a.b. in computer science and global health & health policy. Her academic and research journey reflects a strong interdisciplinary blend of medicine, data science, and global health innovation. with a research portfolio spanning prestigious institutions such as brigham and women’s hospital, mass general brigham, and boston children’s hospital, dr. prasad has contributed to advancements in cardiovascular risk prediction, ai-driven diagnostics, and digital health innovation. Her notable projects include developing machine learning algorithms for early disease detection and ai-powered diagnostic tools, Automated early VTE detection highlighting her expertise at the intersection of healthcare and technology. her scholarly work has been cited 9 times across 6 published documents, demonstrating growing recognition within the academic community, and she holds an h-index of 3, reflecting the impact and relevance of her contributions to biomedical research. driven by a vision to integrate artificial intelligence into clinical decision-making, dr. siona prasad continues to shape the future of computational medicine and global health equity.
Profiles: Scopus | Orcid
Featured Publications
Prasad, S., Dykes, P. C., Schreiber, R., Hijjawi, S., Nawab, K., Kim, A., Lipsitz, S., Syrowatka, A., Samal, L., Bates, D. W., et al. (2025). Development of an algorithm for estimating the likelihood of venous thromboembolism in primary care using structured and unstructured electronic health record data. American Journal of Hematology. Advance online publication.
Rao, A. S., Prasad, S., Lee, R. S., Farrell, S., McKinley, S., & Succi, M. D. (2025). Development and evaluation of an artificial intelligence–powered surgical oral examination simulator: A pilot study. Mayo Clinic Proceedings: Digital Health. Advance online publication.
Alayande, B. T., Pai, M., Prasad, S., Abimpaye, M., Bakorimana, L., Niyigena, A., Nkurunziza, J., Cubaka, V. K., Kateera, F., Fletcher, R., et al. (2023). Image-based surgical site infection algorithms to support home-based post-cesarean monitoring: Lessons from Rwanda. PLOS Global Public Health, 3(2), e0001584.
Prasad, S. (2022, May). Robustness of a visible image machine learning surgical site infection diagnostic algorithm when image quality is degraded. Presented at the Rwanda Health Research and Policy Symposium.
Prasad, S. (2022, April 8). Urban inversions of air pollution sources/sinks and uncertainty quantification to pinpoint determinants of poor air quality. Presented at the Joint Mathematics Meeting.