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GE Healthcare On Thursday he announced that he will partner with Amazon Web Services Build new generative AI models and tools that can efficiently analyze complex medical data.
The healthcare industry generates nearly a third of all data in the world, but much of this information is not easily accessible. Because patient medical records, images, scans, and insurance records are stored in different formats and file systems, it can be difficult for doctors and researchers to sort through this mountain of information, especially on a large scale.
For example, according to a Deloitte report, up to 97% of the data produced by hospitals goes unused. GE HealthCare, which offers medical imaging, ultrasound, patient care and pharmaceutical diagnostic solutions, believes generative AI can help.
The company is collaborating with AWS to create models that clinicians can use to leverage data more efficiently across all healthcare operations, including assessments, diagnostics, decision support, and workflows such as scheduling.
“The tools we hope to develop as a result of this will be aimed at helping hospitals and physicians make the most of the data they have,” Dr. Taha Kass-Hout, global head of science and technology at GE HealthCare, told CNBC in an interview.
Kass-Hout said AWS will likely help GE HealthCare speed up its development and deployment of web-based medical imaging applications, for example, which would provide radiologists and other physicians with easier access to analytics.
GE HealthCare offers its own AI tools, but its partnership with AWS will provide the company with the technical infrastructure needed to quickly build generative AI models and tools at scale. GE HealthCare will use AWS solutions such as Amazon Bedrock and Amazon SageMaker, according to a statement released Thursday.
“Training these models is compute intensive, it's data intensive, it's expertise intensive, and we're collaborating on that,” Matt Wood, vice president of AI at AWS, told CNBC in an interview.
In addition to developing healthcare applications in general, Kass-Hout said GE HealthCare is also exploring how to use generative AI to optimize the company’s internal productivity. He said one of its initial priorities will be to use an assistance tool called Amazon Q Developer to generate real-time code suggestions for its software developers, which should help them work more efficiently.
Kass-Hout said GE HealthCare maintains rigorous testing and standards before bringing products to market, and the same will apply to generative AI applications it develops. GE HealthCare does not train models on customer data, he added.
The company's new models and applications will initially be available to GE HealthCare employees and customers, but the company plans to make them more widely accessible in the future.
