The Ugly Truth about AI in Healthcare

The ugly truth about AI in healthcare is that it is an extremely arduous and challenging technology to tame.  ChatGPT and similar large language models (LLMs) have captured the attention and imagination of the world.  The potential for healthcare is real and worthy of significant excitement and hope.  The reality is that it is a very different AI tool that produces the precise and accurate outputs that are required in most medical use cases than generative AI which covers a staggeringly broad range of topics with only pretty good accuracy.  Healthcare will demand very focused and specific AI tools that require a structured and rigorous training process in order to be fit for purpose.   

In this webinar, our panel of experts will go beyond LLMs to discuss AI’s role in the medical world and the challenges involved. It is easy to get lost in the seemingly endless possibility that AI introduces to the MedTech industry, but it is even easier to get off course in the planning and development of an AI algorithm.

Listeners will walk away with an understanding of…

• Key elements of structing an AI development effort that results in a tool that is fit for a specific purpose
• Important early considerations, get a sense of the order of operations for AI development
• Some unique considerations and trade-offs of developing these tools in the regulated environment