GE HealthCare is teaming with Amazon to help clinicians improve diagnoses using artificial intelligence (AI).
The partnership between GE and Amazon’s Amazon Web Services (AWS) division, announced Thursday (July 25), comes as AI continues to make inroads into the health sector.
In this case, GE HealthCare will use AWS as its cloud provider, with plans to use the company’s healthcare and generative AI services to increase diagnostic and screening accuracy, improve outcomes, provide greater access and equitable care, the company said in a news release.
GE will use Amazon Bedrock, a managed service that provides secure access to the industry’s leading foundation models, to create and deploy “bespoke generative AI applications,” the release said.
The company will also use Bedrock to build its own generative AI applications for healthcare to enhance efficiency and care, GE added.
“With AWS, GE HealthCare plans to use the cloud to deliver more personalized, intelligent and efficient care,” said Matt Garman, CEO of AWS. “GE HealthCare is putting generative AI at the heart of their innovation, accelerated by the investments we have made in healthcare-specific cloud services and generative AI capabilities that provide best-in-class security, data privacy and access to the latest state-of-the-art foundation models.”
The partnership is happening at a moment when AI is making waves in the medical world, with new studies showing the technology’s promise in predicting eye treatment complications, analyzing heart MRIs and developing RNA-based drugs.
“While specialized healthcare AI models demonstrate potential, research also cautions against relying on general-purpose AI chatbots for clinical decision-making, highlighting the need for tailored solutions in critical medical applications,” PYMNTS wrote recently.
The eye treatment study was conducted by researchers from Emory University and Cleveland Clinic, who developed a machine-learning model that examines eye scans to find patients at risk of inflammatory responses to common treatment for age-related macular degeneration (AMD).
The AI model, which analyzed optical coherence tomography (OCT) scans, showed accuracy rates of up to 81% in spotting patients likely to develop a certain post-treatment complication.
Meanwhile, a study by healthcare AI firm Atropos found that popular chatbots like ChatGPT falter in clinical decision-making. Atropos tested five large language models and found they provided relevant information only 2% to 10% of the time.
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