Reyha Verma
Reyha Verma (she/her/hers)
Reyha Verma is an Applied Scientist at Amazon, specializing in Responsible AI. Before joining Amazon, she worked at Arintra, an early-stage startup focused on automating medical coding, where she developed AI/ML pipelines for 4+ major US healthcare systems. Reyha has also gained experience at Sprinklr and PayPal, and holds a Master's degree in NLP from NUS, where she worked on computational social science problems. She is passionate about building technology that drives real-world impact.
Sessions
In this one-hour panel session, AI experts will explore the rapidly evolving impact of these technologies on our society. The discussion will address pressing questions across key domains being transformed by AI: privacy and regulation, environmental implications, economic and labor shifts, and the impact of AI on media and art.
Beyond hearing insightful perspectives from our panelists, you'll have the opportunity to submit your own questions throughout the session. You’ll also have the chance to walk away with prizes, through answering quiz questions based on topics discussed in the session. Whether you're an AI enthusiast, industry professional, or simply curious about how these technologies will shape our world, join us to find out more about this complex area and have your burning questions answered.
Medical coding is essential for healthcare systems, yet it’s often slow and error-prone due to the complexity of translating clinical notes into standardized codes. This challenge is exacerbated by varying coding guidelines, medical jargon, and frequent changes in standards. In this talk, we’ll explore how AI, powered by Python, is transforming medical coding to improve speed and accuracy.
We'll cover Python techniques and libraries - such as LangChain, Transformers, and FastAPI - used to automate the process. You’ll learn about available open-source datasets, pre-trained models, and the role of data annotation in automating medical coding tasks. We’ll also explore whether a purely generative AI approach is sufficient, or if hybrid methods combining traditional coding with AI are more effective. By the end, you’ll understand how Python and AI are improving healthcare workflows, and where the future of AI in medical coding is headed.