Biography
Ashwin Nayak M.D., M.S. is a Clinical Assistant Professor at the Stanford School of Medicine. He completed his M.D. at the University of Illinois at Chicago College of Medicine and Internal Medicine residency at Stanford. He completed his master's degree in Clinical Informatics Management at Stanford University and is board-certified in Clinical Informatics. He has a background in machine learning and app development, and has research interests in large language models, conversational AI and digital therapeutics. He currently practices as an academic hospitalist at Stanford.
View Full Biography
Professional Summary
Education & Certifications
- Board Certification, American Board of Preventive Medicine, Clinical Informatics (2023)
- MS, Stanford University, Clinical Informatics Management (2022)
- Board Certification: American Board of Internal Medicine, Internal Medicine (2021)
- Residency: Stanford University Internal Medicine Residency (2021) CA
- Medical Education: University of Illinois College of Medicine (2018) IL
Administrative Appointments
- Section Chief, Med 7, Stanford University (2022 - Present)
Publications
-
Patient-centered design in developing a mobile application for oral anticancer medications
Crawford, S. Y., Boyd, A. D., Nayak, A. K., Venepalli, N. K., Cuellar, S., Wirth, S. M., & Hsu, G. I.-H. (2019). Patient-centered design in developing a mobile application for oral anticancer medications. JOURNAL OF THE AMERICAN PHARMACISTS ASSOCIATION, 59(2), S586-+. -
A DEEP LEARNING ALGORITHM ACCURATELY DETECTS PERICARDIAL EFFUSION ON ECHOCARDIOGRAPHY
Nayak, A., Ouyang, D., & Ashley, E. A. (2020). A DEEP LEARNING ALGORITHM ACCURATELY DETECTS PERICARDIAL EFFUSION ON ECHOCARDIOGRAPHY. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 75(11), 1563. -
Reactivation of Chagas Disease in a Patient With an Autoimmune Rheumatic Disease: Case Report and Review of the Literature.
Czech, M. M., Nayak, A. K., Subramanian, K., Suarez, J. F., Ferguson, J., Jacobson, K. B., … Blackburn, B. G. (2021). Reactivation of Chagas Disease in a Patient With an Autoimmune Rheumatic Disease: Case Report and Review of the Literature. Open Forum Infectious Diseases, 8(2), ofaa642. -
Visual Recognition Software for Binary Classification and Its Application to Spruce Pollen Identification
Tcheng, D. K., Nayak, A. K., Fowlkes, C. C., & Punyasena, S. W. (2016). Visual Recognition Software for Binary Classification and Its Application to Spruce Pollen Identification. PLOS ONE, 11(2), e0148879. -
Semi-automated segmentation of pollen grains in microscopic images: a tool for three imaging modes
Johnsrud, S., Yang, H., Nayak, A., & Punyasena, S. W. (2013). Semi-automated segmentation of pollen grains in microscopic images: a tool for three imaging modes. GRANA, 52(3), 181–191. -
Comparison of History of Present Illness Summaries Generated by a Chatbot and Senior Internal Medicine Residents.
Nayak, A., Alkaitis, M. S., Nayak, K., Nikolov, M., Weinfurt, K. P., & Schulman, K. (2023). Comparison of History of Present Illness Summaries Generated by a Chatbot and Senior Internal Medicine Residents. JAMA Internal Medicine. -
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records
Fleming, S. L. (2023). MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. ArXiv. -
Use of Voice-Based Conversational Artificial Intelligence for Basal Insulin Prescription Management Among Patients With Type 2 Diabetes: A Randomized Clinical Trial.
Nayak, A., Vakili, S., Nayak, K., Nikolov, M., Chiu, M., Sosseinheimer, P., … Schulman, K. (2023). Use of Voice-Based Conversational Artificial Intelligence for Basal Insulin Prescription Management Among Patients With Type 2 Diabetes: A Randomized Clinical Trial. JAMA Network Open, 6(12), e2340232. -
Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine.
Savage, T., Nayak, A., Gallo, R., Rangan, E., & Chen, J. H. (2024). Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine. NPJ Digital Medicine, 7(1), 20. -
Comparing IM Residency Application Personal Statements Generated by GPT-4 and Authentic Applicants.
Nair, V., Nayak, A., Ahuja, N., Weng, Y., Keet, K., Hosamani, P., & Hom, J. (2024). Comparing IM Residency Application Personal Statements Generated by GPT-4 and Authentic Applicants. Journal of General Internal Medicine.
Clinical Trials
Clinical trials are research studies that evaluate a new medical approach, device, drug, or other treatment. As a Stanford Health Care patient, you may have access to the latest, advanced clinical trials.
Open trials refer to studies currently accepting participants. Closed trials are not currently enrolling, but may open in the future.
Practice Locations
SHC- Hospital Medicine Stanford, CA
Stanford, CAReferring Physicians
PHYSICIAN HELPLINE
Phone: 1-866-742-4811
Fax: 650-320-9443
Monday–Friday, 8 a.m.–5 p.m.
Fax: 650-320-9443
Monday–Friday, 8 a.m.–5 p.m.
Stanford Health Care provides comprehensive services to refer and track patients, as well as the latest information and news for physicians and office staff. For help with all referral needs and questions, visit Referral Information.
You may also submit a web referral or complete a referral form and fax it to 650-320-9443 or email the Referral Center at ReferralCenter@stanfordhealthcare.org.
- Send referrals online
- Place radiology orders
- View referral status
- Access medical records