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Impact AI
Trailer
Bonus
Episode 89
Season 1
Scaling Healthcare Through Virtual Primary Care with Anitha Kannan from Curai
What will it take to bring affordable, accessible, and timely healthcare to all? Curai, an AI-powered virtual clinic, is on a mission to do just that by leveraging AI to enhance the efficiency of licensed physicians through text-based virtual primary care. In today’s episode, I sit down with Anitha Kannan, head of AI and founding member of Curai, to talk about the transformative potential of virtual primary care and its role in scaling healthcare access.
In our conversation, Anitha delves into the technical aspects of using large language models for patient data processing, the challenges of training models with clinical data, and the strategies Curai employs to ensure high-quality care. We also discuss the innovative ways Curai integrates AI into healthcare, the significance of multidisciplinary teams, and Anitha’s vision for the future of virtual care. Tune in for an insightful conversation on scaling healthcare through virtual primary care and learn how Curai is making a real impact!
In our conversation, Anitha delves into the technical aspects of using large language models for patient data processing, the challenges of training models with clinical data, and the strategies Curai employs to ensure high-quality care. We also discuss the innovative ways Curai integrates AI into healthcare, the significance of multidisciplinary teams, and Anitha’s vision for the future of virtual care. Tune in for an insightful conversation on scaling healthcare through virtual primary care and learn how Curai is making a real impact!
Key Points:
- Some background on Anitha Kannan, and how she joined Curai.
- An overview of Curai’s services as a virtual healthcare practice.
- How they provide affordable and timely healthcare access through AI-enhanced systems.
- Machine learning’s role in history taking, information gathering, and summarization.
- How AI streamlines the workflow for physicians.
- Their use of large language models to process patient data.
- Training model challenges: ensuring clinical correctness and handling data omission issues.
- Best practices they’ve developed for validating models and the importance of evaluation.
- Fundamental differences between their work and how other LLMs, like ChatGPT, are trained.
- Their strategy for balancing long-term research aspirations with short-term product development.
- An overview of their multidisciplinary teams and how this contributes to their success.
- Anitha’s hopes for the future of Curai; particularly through partnerships with healthcare organizations.
Quotes:
"Our mission is to provide the best health care to everyone." — Anitha Kannan
“Today, [Carai runs] a text-based virtual primary care practice. We have our licensed physicians or experts in their fields. Then we supercharge them and bring about a lot of efficiencies by leveraging AI.” — Anitha Kannan
"It's very easy to build 80% of a good product with AI today, but I think to get it to 100%, [and] to get it to scale, to be useful in [the] real world — evaluation is the number one thing." — Anitha Kannan
“At Curai, the AI team is composed of clinical experts, subject matter experts, researchers, and machine learning engineers. Every project, long-term or short-term, has a mix of these types of expertise in it. This allows us to work through the problem much more effectively.” — Anitha Kannan
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.
Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.