{"id":161219,"date":"2024-03-27T11:39:00","date_gmt":"2024-03-27T11:39:00","guid":{"rendered":"https:\/\/tecscience.tec.mx\/en\/?p=161219"},"modified":"2024-12-10T17:16:57","modified_gmt":"2024-12-10T23:16:57","slug":"artificial-intelligence-and-breast-cancer","status":"publish","type":"post","link":"https:\/\/tecscience.tec.mx\/en\/health\/artificial-intelligence-and-breast-cancer\/","title":{"rendered":"AI to Predict Breast Cancer Risk"},"content":{"rendered":"\n

Accurately predicting a person’s risk of developing breast cancer is crucial. Health specialists now have various tools, including Artificial Intelligence (AI)<\/a>, which has recently been incorporated.<\/strong><\/p>\n\n\n\n

In 2020, a group of doctors, experts in the detection and treatment of breast cancer from TecSalud<\/a>, tested Mirai, a Deep Learning program<\/a> developed at the Massachusetts Institute of Technology (MIT) specialized in predicting the risk of developing this disease.<\/p>\n\n\n\n

“We used it to evaluate our population with the aim of determining whether this program could predict risk better than traditional tools and if it was applicable to Hispanic populations,” says Daly Avenda\u00f1o<\/a>, a breast radiologist specialist and leader of the study, in an interview with TecScience.<\/em><\/strong><\/p>\n\n\n\n

To do so, they recruited a group of more than 3,000 Mexican women, who were over 40 years old, had good quality mammograms -performed between 2014 and 2017- and a five-year follow-up.<\/p>\n\n\n\n

Mammograms were fed into the program and, with that information alone, Mirai accurately predicted the risk of 76 cases that did result in the development of breast cancer during the years of follow-up.<\/p>\n\n\n\n

The most impressive thing is that, originally, these cases had not been detected by other risk calculation models.<\/strong><\/p>\n\n\n\n

When compared to the Gail model, one of these traditional programs that uses weight, age and family history data to predict the risk of this type of cancer, Mirai had an index of 0.63, higher than the 0.5 index achieved by Gail.<\/strong><\/p>\n\n\n\n

\u201cMirai identifies patterns that are invisible to the human eye and can assess risk very precisely,\u201d says Avenda\u00f1o.<\/p>\n\n\n\n

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