AI analysis of breast cancer is 30 times faster than humans, and the accuracy rate is 99%

Release date: 2016-09-22

Researchers have developed a machine learning software that accurately diagnoses the risk of breast cancer in patients 30 times faster than doctors based on breast film results and personal medical history.

The system can help doctors better diagnose breast cancer, which means fewer times of mammogram callbacks and false positives. Stephen Wong, from the Houston Methodist Institute, is one of the researchers. He said: "This software can intelligently check millions of cases in a short period of time, which allows us to use the patient's breasts more effectively. Tablet to determine the risk of breast cancer. It can avoid unnecessary biopsy."

Mammogram refers to mammogram, which is to find potential cancer cells before any symptoms appear. In many countries, women over the age of 50 are advised to do preventive screening every two years. Although such preventive screening is good, there are 50% of the tests in the United States that have false positive results. In other words, one in every two healthy women was wrongly told that they might have cancer.

In addition, “suspicious” breast radiographs also have a large gray area with a cancer risk of between 3 and 95 percent. These patients are generally recommended for subsequent biopsies. Researchers say that about two percent of current biopsies in the United States are unnecessary. The new AI is able to produce accurate results on the first screening, greatly reducing this number.

Computer software has been used by doctors to take images of the mammogram, but this system goes a step further by analyzing the doctor's report and the patient's complete medical history during the scan to more accurately determine the probability of breast cancer.

In a recent demonstration, the researchers used this AI to test the results of mammography and pathology of 500 breast cancer patients. The software gives diagnostic information within a few hours, and it also highlights the type of breast cancer subtype for each patient. The researchers compared the results of AI with clinical results and found that its accuracy reached 99%. It takes more than 500 hours for a doctor to get the same analysis.

Wong said: "In the absence of AI, accurate assessment of many forms is simply not possible."

It needs to be clarified that the AI ​​has not been tested in the real world so far, and the analysis results of this study are from existing breast cancer patients. However, the researchers have now provided enough evidence to guarantee the next test.

The AI ​​also does not prevent all false positives and suspicious breast radiographs, and sometimes insufficient information can not be diagnosed. But it should help doctors reach more accurate conclusions. We look forward to seeing this software make breast cancer diagnosis faster and more accurate, thus saving people from unnecessary follow-up tests. The study has been published in the Journal of Canser.

Source: Omelette Net

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