Teen Develops Less Invasive Means to Detect Breast Cancer

A 17-year-old from Sarasota, Florida may have just changed how breast cancer gets diagnosed.

Brittany Wenger won the grand prize at the 2012 Google Science Fair — announced in July 2012 — for building an artificial neural network that can detect breast cancer malignancy from fine needle aspirate samples with nearly 99 percent accuracy.

Her approach was ingeniously simple in concept: she trained a cloud-based neural network on thousands of samples, teaching the "artificial brain" to recognize the patterns that distinguish malignant tissue from benign. The result was a diagnostic aid that could make early, less invasive detection far more reliable — potentially sparing patients unnecessary biopsies and catching cancers sooner.

Wenger taught herself the programming and trained her network through millions of test iterations. For her work, she took home the fair's top honors, including a $50,000 scholarship.

Her win was part of a remarkable year for teen science: the Google Science Fair's 2012 finalists included projects on everything from cancer detection to environmental cleanup. But Wenger's stood out for tackling one of medicine's hardest pattern-recognition problems with tools she largely taught herself — a reminder that the next breakthrough in cancer detection might come not from a lab, but from a teenager with a laptop and a question.

This article is for general information only and is not medical advice.