Student Spotlight: Ashraya S.
As a participant of the Stanford AIMI Bootcamp, I was introduced to so many new aspects of AI and machine learning in healthcare.
From the guest lectures to the coding tutorials, every moment of the bootcamp provided an opportunity for me to learn more. I gained a new perspective on healthcare during the first lecture by Dr. Kevin Schulman. Previous to this, I hadn’t thought much about how healthcare systems worked, but this lecture made me realize the importance of economics and budgeting in healthcare. The deep dive of the history of health insurance in the US helped me understand medicare and medicaid, and how healthcare works nationally. This lecture sparked an interest in me about care in the government.
My favorite part of the experience was the ‘Meet the Experts’ portion of the day. I particularly enjoyed Dr. Geraldine Dean and Dr. Xuan Zhao’s talks. Dr. Dean talked about implementing AI tools into hospital settings, explaining the path she took to get to where she is now. She told us to start our journey with cold calls and emailing, seeking help, breaking boundaries, and persisting. As someone who runs a podcast, this advice was so important to me because cold emailing and messaging is the most important part, yet the hardest, of what I do. Dr. Zhao expanded on the importance of AI in behavioral sciences, talking about human and AI interactions. Her talk stood out to me because I’m interested in studying neuroscience in the future, so I thought her insights were very relevant. She shared how to maintain mental health through her STAR method, introducing her AI powered mental health tool, Flourish Science. I loved and could relate to the mission of her tool on a deeper level while also connecting the marketing strategies she used for her app for my podcast. Both speakers showed me a completely different view of AI in health, whether it was related to mental health or radiology. Still, even though Dr. Zhao and Dr. Dean’s talks were the highlights of my experience, all of the experts’ friendliness and understanding of students wanting to pursue AI in healthcare gave me the chance to connect with them via email and linkedin.
On top of this, another part of the bootcamp that I will remember was the coding tutorial from one of the student leads, Hadil. I had actually completed a project similar to this using CNNs last year for my county science fair, for the detection of Parkinson’s disease, but the accuracy of my results was not as high as I hoped because my train/test sets were incorrectly labeled. Through the coding tutorial, I was introduced to new deep learning methods like Random Forest Classifiers. Now, I also have a pneumonia dataset that I can use for future projects!
After completing this program, I realized how important it is for AI datasets to be diverse and bias-free. There have been times when AI has not been able to accurately detect different diseases in minorities, such as African Americans, because there wasn’t enough data to train the model. This emphasizes the need to adapt datasets. Relating to this, I want to focus specifically on diversifying datasets that are used for brain imaging. Models that are used to detect neurological conditions like Parkinson’s or Alzheimer's need to be very accurate because the brain is so complex, so there is very little room for error. This starts with high-quality data and datasets. This area of AI in medical imaging particularly interested me because my grandfather has Parkinson's disease, and I hope to play an influential role in helping patients that experience struggles similar to my grandfather’s.
This bootcamp opened my eyes to the complex and intricate world of AI and machine learning in healthcare. This experience has motivated me to look for more opportunities to expand my understanding in this topic. I am so grateful to have been a part of this program.
- Ashraya S, AIMI '25 Summer Health AI Bootcamp Participant