Salesforce, in collaboration with the clinicians at the Lawrence J Ellison Institute for Transformative Medicine of USC, invented a new system that has the ability to spot signs of breast cancer. This Artificial Intelligence tool vouches to detect the signs with an impressive accuracy of 92%.
The new Artificial Intelligence tool, named ReceptorNet, can make the treatment of breast cancer more readily available and less expensive
Named as ReceptorNet, the AI system can determine a biomarker that will prove to be instrumental in choosing a suitable treatment for breast cancer. In the journal, Nature Communications, the study stated that ReceptorNet can pave way for treatments that are more readily available and affordable. The study is a joint effort of the Salesforce team and Dr. Agus, CEO of the University of Southern California.
Generally, doctors extract breast cancer cells during the surgery or biopsy. These are then tested to check if they contain proteins that pose as hormone (estrogen or progesterone) receptors. When the hormones attach to the receptors, they stimulate the growth of cancer. In the case of ReceptorNet, the algorithm predicts the status of hormone receptors from the tissue’s images, offering results within an inexpensive environment.
Every year, breast cancer impacts nearly 2 million women. The rates are on the rise every year around the globe.