New AI Architecture Can Detect Breast Cancer With a Near-Perfect Accuracy Rate
BioE Assistant Research Professor Saeed Amal and his research team have developed a new AI architecture that has detected breast cancer with a 99.7% accuracy rate. His research was published in the journal Cancers. He has submitted an invention disclosure with the Center for Research Innovation on the idea.
This article originally appeared on Northeastern Global News. It was published by Cesareo Contreras. Main photo: The median age for a breast cancer diagnosis is 62, according to the American Cancer Society. (Press Association via AP Images)
Can AI help with breast cancer diagnoses? Northeastern researchers develop new system that is nearly 100% accurate
Earlier this year, Northeastern University researchers unveiled a web-based artificial intelligence tool designed to diagnose prostate cancer at a faster and more accurate rate.
Now, the same group, led by bioengineering professor Saeed Amal, has developed a new AI architecture designed to detect breast cancer that the researchers say has achieved an accuracy rate of 99.72%.
Breast cancer accounts for 30% of new female cancer cases each year, and in 2024, an estimated 42,500 women will die from it, according to the American Cancer Society.
Research on the findings was recently published in the journal Cancers.
These projects are part of a larger effort by Amal to create an online framework doctors can access to diagnose a range of cancers using these innovative AI technologies. Amal says the new tool will “redefine digital pathology.”
He and his team recently submitted an invention disclosure with the Center for Research Innovation on the idea.
“The AI would look at the high-resolution images and would learn from historical data how to identify cancer patterns and perform diagnoses,” he says. “The AI can’t miss a tumor in the biopsy and won’t be exhausted after diagnosing 10 or 20 people.”
Read full story at Northeastern Global News