Artificial intelligence Google diagnose breast cancer better than doctors

Left sample view of a slide containing lymph nodes with multiple artifacts the dark zone on the left is an air bubble the white streaks are cutting artifacts the red hue across some regions are hemorrhagic, the tissue is necrotic

Human pathologists can miss these as much as 62% of the time when under time pressure, studies have shown.

The team trained its algorithm (Lymph Node Assistant, aka LYNA) to recognize the characteristics of tumors using two sets of pathological slides, giving it the ability to spot metastasis in a wide variety of conditions.

Cancer, a disease caused by the growth of abnormal cells beyond their usual boundaries, is the second leading cause of death worldwide, according to the World Health Organization.

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

Also last February, scientists from Google and Verily have created a medical machine based on mechanical learning and can accurately export basic information about an individual, including age and blood pressure, and if he or she is in danger of suffering a major a heart attack, such as a heart attack.

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Despite misidentifying giant cells, germinal cancers and histiocytes, LYNA managed to perform better than a pathologist.

The scientific report published on this issue explains that: "Artificial Intelligence Algorithms can exhaustively evaluate each occurrence, individually and in detail". For comparison, pathologists are on average 81pc accurate at detecting these cells when under time constraints. "We provide a framework to aid practicing pathologists in assessing such algorithms for adoption into their workflow (akin to how a pathologist assesses immunohistochemistry results)". The Google AI tool used a 299-pixel image as input, highlighted tumors at the pixel level and extracted labels of the tissue patch.

Even though the Google AI tool is yet to be used in real-life clinical situations, doctors are acknowledging its usefulness and how its role can be expanded.

Because of the extremely reliable diagnosis, the AI system enables doctors to do more caring for the patient rather than worrying about the diagnosis stage.

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