San Antonio Symposium to Feature AI in Breast Cancer

The 49th San Antonio Breast Cancer Symposium will highlight artificial intelligence and digital pathology research in early-stage breast cancer.

Updated on Nov. 2, 2026 in Cancer

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The 49th San Antonio Breast Cancer Symposium will feature more than 11,000 attendees and sessions on AI and digital pathology for early-stage breast cancer over five days. AI Illustration. Upload story photo >

The 49th San Antonio Breast Cancer Symposium will feature abstracts on AI and digital pathology for early-stage breast cancer over five days. The meeting is expected to draw more than 11,000 attendees.

Why it matters

Digital pathology photographs a tissue specimen and transmits the image for analysis, which could make testing faster and less expensive. Researchers expect its information may match or exceed data from genomic assays on tumor specimens.

The symposium is in its 49th year and is expected to draw more than 11,000 attendees over five days. Results of the digital pathology abstracts have not yet been reported.

The players

San Antonio Breast Cancer Symposium

A long-running annual breast cancer research meeting held in San Antonio, now in its 49th year.

Virginia Kaklamani

A co-director of the San Antonio Breast Cancer Symposium who is affiliated with UT Health San Antonio.

The details

The symposium includes educational sessions, state-of-the-art sessions, and a debate on T-DXd use in neoadjuvant versus adjuvant settings for early-stage HER2-positive disease. Special sessions will address lobular carcinoma, obesity and breast cancer, and GLP-1 agonists.

Timeline

  1. The meeting runs for five days, with an article previewing it published November 2, 2026.

Big Picture

The 49th San Antonio Breast Cancer Symposium continues a decades-long annual series, and this edition extends that role by spotlighting AI and digital pathology in early-stage breast cancer.

If digital pathology tests become faster and cheaper, patients with early breast cancer may receive quicker diagnostic results. Whether this reaches clinics widely has not been established.

The takeaway

Patients and families following breast cancer care can watch how AI-based pathology tools move from research presentations into routine testing. Discussing new diagnostic options with a treating oncologist remains the most practical next step.

Further reading

For more on breast cancer research, explore the Cancer section.

Source note: This article includes information reported by MedPage Today.