When Jake O’Leary at Microsoft first got his hands on Generative AI (GenAI) last year, he immediately knew it was going to be a game-changer. The corporate VP of Healthcare Solutions, Azure Cloud & AI, told our Next Generation Healthcare Summit audience he’s seen slow incremental creations, changes, and improvements over the years, but this he called a “once in a lifetime moment.” An overnight transformational innovation creating endless opportunities in healthcare from drug discovery, remote patient monitoring, and reducing manual tasks and inefficiencies.
- Generative AI is reducing documentation burden
- Relieving clinician burnout
- Humans control the output reducing risk
Generative AI: Taking the world by storm
Artificial intelligence (AI) is now creating content from simple words and context. A multi-modal output producing text, code, images, videos, music, speech, and game backgrounds. GenAI models are often known as large language models (LLMs) or foundation models, while Generative Pre-Trained Transformer (GPT) is a family of language models that use deep learning techniques to generate natural language text. By connecting with these models’ APIs, companies can build applications with easy interfaces for specific tasks, increasing accessibility.
Generative AI capabilities:
Jake asked GenAI to list its capabilities and it responded with context generation, anomaly detection, data augmentation, personalization, text summarization, and language translation. Specific to healthcare, Jake doubled back on content generation and text summarization.
Content generation includes:
- Generate Complex Documents
- Steered with nuanced instructions
- Instruct and annotate in any language, slang, dialect
Text summarization includes:
- Create structured data from unstructured text
- Summarize content, both structured and unstructured
- Generate transcript summaries
GenAI allows a human to generate content and documents in a natural language way. Conversations between clinicians and patients can now be captured, reducing inefficiencies and lost data. As Jake told our payer and provider audience, “Generative AI allows for summarization and interpretation and discovery by leveraging these data sets at scale and you can also use it to generate a summary of a conversational transcript from this data, so in the case of healthcare this is what’s going to unleash massive amounts of innovation by lowering the bar for developers and start-ups and provider organizations and professional organizations to create innovations without having to solve some of the hardest problems in healthcare in terms of how do we normalize the data?”
Generative AI models: Things to consider
Risk mitigation layers for generative AI
Jake is currently taking a deeper look at the safety system around GenAI, to allow filtering and monitoring of inputs and outputs and creating additional controls. This will ultimately steer and fine tune the underlying models themselves which is helping to deter abuse. Jake said, “it’s simply a set of capabilities and additional AI models that sit in front of the generative AI model to better look at the prompts coming in and the output coming out of the Generative AI model, allowing users to detect hate or personal information that may be flowing in and out of the model, it allows for ways in which to control bias, unwanted information, or abuse without changing the core model itself.”
Copilots: Human Assisted Generative AI
Microsoft will soon introduce DAX Copilot fully automated clinical documentation. It is a natural language interface. It can be text, voice or even a chatbot but ultimately humans are guiding and approving the output. As Jake concluded, “we are changing clinicians lives helping them with documentation burden and I can say from the results we are getting, it has changed results for providers. Allowing them to complete their clinical documentation that same day and go home that night with notes all complete. Its fundamentally a game changer for healthcare.”
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