Google's AI can spot breast cancer better than humans

Doris Richards
October 17, 2018

Metastatic tumors and cancer cells escaping from their tissues of origin travel through the circulatory system or lymphatic systems and form new tumors in other parts of the body and are hard to detect.

"Artificial intelligence algorithms can exhaustively evaluate every tissue patch on a slide", Google's paper read.

Google's findings were cited in two medical journals, the Archives of Pathology and Laboratory Medicine and the American Journal of Surgical Pathology.

More specifically Google AI was used to detect advanced (metastatic) breast cancer, with the company noting that it could do so with greater accuracy than human pathologists can.

US tech giant Google has created a tool that could potentially help doctors to diagnose breast cancer using artificial intelligence (AI). Human pathologists miss small metastases on individual slides as much as 62% of the time when under time constraints.

In addition to accuracy, thanks to LYNA's speed, the inspection time has been reduced to one single minute.

In a new study, titled "Artificial Intelligence Based Breast Cancer Nodal Metastasis Detection", researchers outline how an AI called LYNA (short for "Lymph Node Assistant") can be trained how to spot breast cancer that has metastasized (spread beyond its original location) and compromised the lymph nodes, which are a system of tubes spread across the body that help filter and fight harmful substances.

For now, LYNA has not yet been used in real-life clinical situations but the scientists believe that they can find further use in the AI and train it to search for other types of tumors as well. When it is ready for practical use, it could lead to more accurate diagnoses and free up doctors to focus more on treating patients.

Google is investing in health care applications for artificial intelligence. Additionally, Verily, which is Alphabet's life sciences subsidiary, is developing a system that determines a person's risk of heart disease using retinal scans.

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