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GE Healthcare announced on Thursday Amazon Web Services Build new generative artificial intelligence models and tools that can effectively analyze complex medical data.
The healthcare industry generates nearly one-third of the world’s data, but much of this information is not easily accessible. Because patients’ medical records, imaging, scans and insurance records are stored in disparate file formats and systems, it can be challenging for doctors and researchers to sort through this mountain of information—especially on a larger scale.
For example, according to one report, as much as 97% of data generated by hospitals is not used. Deloitte. GE HealthCare, which provides medical imaging, ultrasound, patient care and drug diagnostics solutions, believes generative artificial intelligence can help.
The company is working with AWS to build models that clinicians can use to more effectively leverage data in healthcare operations, including workflows such as screening, diagnosis, decision support and scheduling.
“We expect that the tools built out of this will be designed to help hospitals and clinicians make the most of the data they have,” Dr. Taha Kass-Hout, global chief science and technology officer for GE Healthcare, told CNBC in an interview.
Kass-Hout said AWS could help GE HealthCare accelerate the development and deployment of web-based medical imaging applications that would make analysis more accessible to radiologists and other doctors.
GE HealthCare provides 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 news release Thursday.
Matt Wood, vice president of artificial intelligence at AWS, said in an interview with CNBC: “Training these models requires a lot of computing, a lot of data, a lot of expertise, and we are collaborating on this.”
In addition to building broader healthcare applications, GE HealthCare is exploring how to use generative AI to streamline the company’s internal productivity, Kass-Hout said. He said one of its first priorities will be to use an auxiliary 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, as does the generative AI applications it develops. GE Healthcare does not train models on customer profiles, he added.
The company’s new models and apps will initially be available to GE HealthCare employees and customers, but it plans to make them more widely available in the future.
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