Given the great technological advances that exist today regarding the diagnosis of breast cancer and the arduous campaigns that seek that more women know how to detect it on time, the two main ways for effective treatment and the possibility of cure continue to be breast self-examination. and the mammogram.
However, there could be a change and a great advance in terms of early detection, since researchers from Massachusetts, United States, discovered that with the help of a device with Artificial Intelligence (AI) breast cancer could be predicted up to five years after it begins to manifest.
This inference arose from research conducted by scientists at the Massachusetts General Hospital and the Massachusetts Institute of Technology (MIT) Science and Artificial Intelligence Laboratory, who, after developing a prediction model based on learning deep (deep learning), detected subtle patterns that could predict the chances of cancer development.
The researchers tested this technology on 90,000 mammogram results from just over 6,000 patients at Massachusetts General Hospital, which were performed from 2009 to 2012. The analysis was based on changes in breast tissue, which are believed to be be the precursors of cancer, in order to avoid confusion regarding hormonal and biological factors.
Artificial intelligence predicted 31 percent of cases in high-risk patients, representing a significant improvement in disease prevention, as previous traditional techniques could only predict 18 percent of these cases.
This AI method, developed by Professor Regina Barzilay, was able to recognize subtle patterns in breast tissue. The advance could foresee the possibilities of suffering from it up to five years of manifesting symptoms. In addition, in the future, it will allow the creation of more personalized treatments and will facilitate follow-up, adapting to the specific needs and risks of each patient.
This scientific advance will be equally effective for any race, since the model has been tested in people with racial differences, in order to have a more accurate detection of the disease and, with it, revolutionize early diagnosis for better care. medical.