Technology is a fundamental part of today’s world and its impact can be seen in all areas. Among the most important innovations that exist is Artificial Intelligence, but the most important thing is to know how it can help identify diseases such as breast cancer from its early stages.
In Latin America alone, each year more than 462 thousand women are diagnosed with this type of tumor, which is becoming more and more common. While it is estimated that patients who receive medical care in the early stages have up to a 90 percent chance of beating it.
Benefits to find the best treatment for each patient
With the goal of solving the world’s toughest health problems, Massachusetts General Hospital, owned by Mass General Brigham, has worked to implement active surveillance programs to monitor early-stage breast cancer and help patients to avoid unnecessary surgeries and radiation.
Manisha Bahl, Doctor of Medicine and Public Health at Harvard University and researcher at Massachusetts General Hospital, has developed an Artificial Intelligence tool to identify women with early breast cancer who may be candidates for this type of treatment.
“I am studying early stage breast cancer. The growing concern about over-treating this type of cancer has led us to active surveillance trials in which surgery and radiation are avoided, and imaging is used to monitor the disease. “
For the success of these programs, it is essential to carefully select patients who meet the necessary parameters. This research seeks to develop a tool to identify women with low-risk breast cancer, who are suitable candidates for active surveillance.
How does it work?
In this way, the tool would combine clinical, pathological and image data that, thanks to state-of-the-art technology, allow deep and automatic learning of each case. The project is also collaborating with artificial intelligence experts from the Massachusetts Institute of Technology and is funded by the National Institutes of Health.
According to Manisha, there is controversy over the management of high-risk breast lesions, which has led to multiple variations in patient care, with some women undergoing surgery and others undergoing imaging surveillance. Using the tool will allow women with early stage breast cancer to make more informed decisions regarding their treatment options.
Massachusetts General Hospital and the Massachusetts Institute of Technology used historical data from more than 1,000 women with high-risk injuries to develop this AI-based model. With it, it could help identify which women with high-risk injuries would benefit the most from surgery and who could be safely followed by imaging.
The Pan American Health Organization (PAHO) foresees an increase of 34 percent in women diagnosed with breast cancer by 2030. Therefore, the use of tools as advanced as this one, would not only allow the effectiveness of the treatments, but would also help reduce breast surgeries. unnecessary breast and increase the range of possible treatments to follow.