What happened
Artera of Los Altos, California, developed ArteraAI Breast, deep learning software that reads a digitized H&E slide of a breast resection. It adds the patient's age, tumor size and nodal status and estimates the risk of distant metastasis in HR+/HER2- early breast cancer. The model was trained on slides from 8,549 patients in four trials. FDA reviewers describe a retrospective validation in 1,271 patients diagnosed between 2006 and 2019 at three US sites. Five-year metastasis risk was 8.7% in the high risk group and 0.9% in the low risk group, against 3.6% for all patients. At ten years the figures were 16.6%, 2.8% and 7.6%. FDA cleared the software on 4 May 2026. The study tested how well the groups separate risk and did not test whether care guided by the software changed outcomes. In the high risk group, five-year risk was 6.4% for African American patients and 9.7% for White patients.
Sources
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Regulatory document, by authors with no tie to the system.
5-year risk of DM for ArteraAI Breast Risk category High (8.7%) is statistically significantly higher than the overall risk (3.6%) and this difference (5.1%) is clinically significant.
Details
AI system
- Workflow
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Slides from treatment-naive breast resections were stained with H&E and scanned on a Philips Ultra Fast Scanner or a Leica Aperio GT450 DX. Physicians supplied the patient's age, tumor size and nodal status.
Follow-up
- Conditions for replication
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The patient is an adult with HR+/HER2-, N0 or N1 early-stage invasive breast cancer who is a candidate for adjuvant therapy. A pathologist confirms cancer on the slide and releases the report.
Entry details
- Sector
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Healthcare.
- Purpose
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Artera built ArteraAI Breast to give physicians five- and ten-year risks of distant metastasis for prognostic decisions in early breast cancer.
Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, AI contribution, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.
Cite this record
Peter H. Vartanian. (2026). ArteraAI Breast sorted breast cancer patients by risk of spread (AIBD-0799). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0799.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)