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GPT-4 in a Cancer Center: Challenges and Lessons from Dana-Farber’s Deployment
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GPT-4 in a Cancer Center: Challenges and Lessons from Dana-Farber’s Deployment

Last Updated on April 2, 2024 by Editorial Team

Author(s): Dr. Mandar Karhade, MD. PhD.

Originally published on Towards AI.

HealthCare Generative AI and Production Hiccups — welcome!

Artificial intelligence (AI) has woven its way into the fabric of healthcare over the past few decades, evolving from basic predictive models to sophisticated generative systems like Large Language Models (LLMs). These advancements have spurred significant interest in their potential applications across various medical domains. Dana-Farber Cancer Institute GPT4 deployment offers a unique glimpse into the practical challenges and lessons learned in integrating cutting-edge AI within a complex healthcare setting.

The integration of LLMs into healthcare has shown promise, with applications ranging from medical documentation to decision support systems. However, deploying these models, particularly in sensitive fields like healthcare, requires careful navigation of technical, ethical, and regulatory landscapes. The Dana-Farber Cancer Institute embarked on this journey with a clear vision: to harness the potential of GPT-4 to enhance operational efficiency and research capabilities while maintaining strict adherence to privacy and ethical standards.

Source: Interface developed by Dana Farber’s Institute

Dana-Farber’s GPT4DFCI project aimed to implement a private, secure, and HIPAA-compliant instance of GPT-4 through the Azure-OpenAI API endpoint. The initiative was grounded in a comprehensive governance framework, emphasizing the need for a controlled and ethical use of AI. The technical deployment focused on creating a user-friendly interface, ensuring data security, and establishing robust… Read the full blog for free on Medium.

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Published via Towards AI

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