About me
Born into a family of doctors, I discounted medicine as a profession until I worked at a free clinic near my college. I realized that even in my adopted country of the US there were wide gaps in access to quality healthcare. I pursued becoming a doctor to help change that and through that journey found I enjoyed building healthcare startups.
Now I head product at Clinikk where we are re-imagining healthcare for an aspiring India. Previously, I helped develop and deploy some of the first machine learning-integrated clinical workflows at Duke and Stanford for surgery and palliative care (featured in STAT, GAO and NAM publications). I got started in healthcare data science setting up Impact Evaluation at Noora Health (YC W13). I also helped optimize India's national public digital health platform for non-communciable chronic diseases as a India Digital Health Net fellow at Harvard.
I live in 📍 Bangalore, India, and I strongly believe India will leapfrog in healthcare. (🗣 Seh-hedge)
🧑🏽💻 Projects
2023 - PaCo - an AI assistant for doctors and patients [Demo]
2018 - Risk Calculator for Post-operative surgical complications [App]
2017 - Data Explorer for the National Family Health Survey Data Explorer [App]
GPTs
🎥 Youtube Series
April 2024 - Better Clinician-AI collaboration via Disagreement [Video]
Nov 2023 - MedAlign to create the perfect ChatGPT for doctors [Video]
Feb 2023 - Google's MedPaLM for medical question answering [Video]
🎙️ Talks
Nov 2023 - A Clinician's Primer to Medical AI (w/ Academy of Family Physicians India) [Slides]
May 2023 - India Angel Network Generative AI in the Healthcare Industry [Talk][Slides]
May 2020 - Integrating predictive models into the clinical setting [Slides]
✍🏼 Essays
Aug 2023 - Beyond AI - technology to scale quality healthcare in India [Blog]
Jul 2021 - Which are top funded startups and key investors in healthcare in India? [Blog]
🎓 Education
MD Doctor of Medicine, Duke University School of Medicine
MS Biomedical Informatics, Stanford University Department of Biomedical Informatics
BS Biomedical Engineering, Cornell University College of Engineering
🗞️ Selected Papers
[Google Scholar] [CV]
Public comments to NDHM consultation papers [HFR] [HPR] [UHI] (2021) India Digital Health Net (🔗)
A survey of extant organizational and computational setups for deploying predictive models in health systems. Kashyap, S., Morse, K. E., Patel, B., & Shah, N. H. (2021). Journal of the American Medical Informatics Association. [Slides]
Machine Learning for Predictive Analytics. Sehj Kashyap, Kristin Corey, Aman Kansal and Mark Sendak in Machine Learning in Cardiovascular Medicine, pg 45-69.
A framework for making predictive models useful in practice. Jung, K., Kashyap, S., Avati, A., Harman, S., Shaw, H., Li, R., Smith, M., Shum, K., Vetteth, Y., Seto T, Bagley, S.C., & Shah, N. H. (2021). Journal of the American Medical Informatics Association, 28(6), 1149-1158.
A path for translation of machine learning products into healthcare delivery. Sendak, M., D’Arcy, J., Kashyap, S., Gao, M., Nichols, M., Corey, K., Ratliff, W., & Balu, S. (2020). EMJ Innov, 10, 19-172.
Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): a retrospective, single-site study. Corey K*, Kashyap S*, Lorenzi E*, ... & Sendak, M. (2018). PLoS medicine, 15(11), e1002701. [Slides]