Dr. Naila Camila da Rocha | Medicine and Health Sciences | Best Researcher Award
University of Wisconsin-Madison | United States
Dr. Naila Camila da Rocha is a distinguished researcher specializing in biostatistics, artificial intelligence in healthcare, and predictive analytics, with a strong focus on advancing precision medicine and healthcare delivery. She is completing her Ph.D. in Biometrics at São Paulo State University (UNESP) in collaboration with the University of Wisconsin–Madison, following a Master’s in Biometrics, a Professional Master’s in Applied Statistics, and a Bachelor’s in Administration. With over 14 years of experience in strategic planning, business intelligence, and applied statistics, she has held leadership roles including Head of Growth Strategy and Revenue at iFood, Data Science Manager at BRF, and currently works as a Data Scientist at Statbit, while also contributing as a volunteer researcher at the Clinics Hospital of Botucatu (LabData). Her research applies machine learning, natural language processing, and advanced statistical modeling to nephrology, transplantation, and chronic disease management, with impactful results such as predictive models for graft rejection, delayed graft function, and inequities in hemodialysis access. She has published more than 20 peer-reviewed papers in high-impact journals and received multiple prestigious awards, including the Massola Award (2025), AACD Summit Award (2025), Magaldi Award (2023), and Nestor Schor Award (2023). By successfully bridging data science with clinical applications, she has established herself as an influential voice in developing innovative tools for early diagnosis, risk stratification, and health system optimization, demonstrating excellence as a researcher whose work is shaping both academic knowledge and practical healthcare solutions.
Profile: Google Scholar | ORCID
Featured Publications
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Beltramino, L., Bedacarratx, V., Roldán, P., González, N. A. M., … (2020). Aprendizajes y prácticas educativas en las actuales condiciones de época: COVID-19. Universidad Nacional de Córdoba, Facultad de Filosofía y Humanidades. Cited by: 33
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Da Rocha, N. C., Barbosa, A. M. P., Schnr, Y. O., Machado-Rugolo, J., … (2022). Natural language processing to extract information from Portuguese-language medical records. Data, 8(1), 11. Cited by: 13
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De Andrade, L. G. M., Barbosa, A. M. P., Da Rocha, N. C., Cardoso, M. M. de A., … (2022). Impact of the COVID-19 pandemic on solid organ transplant and rejection episodes in Brazil’s Unified Healthcare System. Journal of Clinical Medicine, 11(21), 6581. Cited by: 11
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Ordones, F. V., Kawano, P. R., Vermeulen, L., Hooshyari, A., Scholtz, D., … (2025). A novel machine learning-based predictive model of clinically significant prostate cancer and online risk calculator. Urology, 196, 20–26. Cited by: 5
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Addad, V. V., Palma, L. M. P., Vaisbich, M. H., Barbosa, A. M. P., … (2023). A comprehensive model for assessing and classifying patients with thrombotic microangiopathy: The TMA-INSIGHT score. Thrombosis Journal, 21(1), 119. Cited by: 5
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Santos, G. P. A., Sesso, R., Lugon, J. R., Neves, P. D. M. de M., Barbosa, A. M. P., … (2024). Geographic inequities in hemodialysis access: A call to reassess dialysis facility locations in Brazil. Journal of Nephrology, 37(9), 2601–2608. Cited by: 4