Google has announced that it has teamed up with iCad, (a health care provider that’s known for innovative cancer detection and therapy solutions) and licensed its AI tech for breast cancer and personalised risk assessment, reveals a report by The Verge.
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The new association will allow iCAD to apply the licensed technology to further improve its 3D and 2D AI algorithms and will commercialise developed products.
Greg Corrado, head of Health AI, Google. Corrado also said that Google Health’s AI tech could enable healthcare to be more available, accessible, and more accurate.
He highlighted in a blog post that the entire ecosystem needs to work in tandem to better healthcare solutions that could serve patients, doctors and clinicians better.
iCAD is looking to fuse Google’s mammography AI research model into iCAD’s existing tools. One of them is its ‘ProFound AI’ tool which analyses images from digital breast tomosynthesis (DBT). The tool essentially scans DBT images to look for malignant soft tissue densities and calcifications.
iCAD is also expected to use Google’s AI model with its risk evaluation tool that as per Google’s claims would offer personalised breast cancer risk estimation, specific to individuals.
Corrado said in a statement, “iCAD’s breast imaging portfolio of tools and Google Health’s mammography AI technology give radiologists the opportunity to focus on their patients.”
iCAD will also harness Google Cloud’s scalable infrastructure, offering them the ability to expand cloud-hosted solutions into new regions.
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“By doing so, iCAD can scale access to AI-based tools in underserved regions where infrastructure challenges may constrain their ability to offer breast cancer screenings,” he added.
Google is also working with partners to design studies where AI is implemented to support real screening systems to better understand if the technology could help in a clinical workflow.
For instance, it is currently collaborating with Northwestern Medicine where it is looking at how its tech can help prioritise high-risk cases and reduce the diagnosis time for screened individuals.
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