Breast cancer prevention with artificial intelligence

Adam Yala works with technology that can improve breast cancer detection thanks to artificial intelligence.

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Adam Yala works with technology that can improve breast cancer detection thanks to artificial intelligence.


Adam Yala is a young student at Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Laboratory. At just 24 years of age, he has managed to develop an efficient, non-invasive and inexpensive system to detect and prevent breast cancer.

Yala initially focused on machine learning (automated learning) with projects that allowed him to carry out research on language processing. This even led to a collaboration with the FBI. Further down the line, he realised the possibilities of image processing and automated machine learning in medicine and disease prevention. As a result, he started developing medical tools in partnership with the Massachusetts General Hospital (United States).

Through this collaboration arose the project he is currently working on. At first the team, which Yala featured as a member of, focused on incorporating all knowledge of this disease into a single database. Thanks to language processing techniques, they gathered as many as 16, 000 scientific articles, that can now be more easily consulted.

The next step of the project has been working to improve cancer detection and rendering it cheaper and more accessible to the whole population. So far early diagnosis in at-risk people has been carried out based on factors such as age, origin and family history. According to Yala, these indicators “are very important but haven’t been updated in 20 years”.

The team’s work consists of “making them more specific to women and finding common patterns”. In order to do so, they have created an artificial intelligence system that works with information provided by collaborating hospitals. They have developed a database of common patterns that facilitates identification of possible breast cancer cases.  The role of this system is to work as an intermediary before the intervention of a medical specialist. To this end it identifies mammograms that have detected possible breast cancer in patients.

Currently, it is a doctor who determines what illness a patient has and what kind of treatment is most appropriate. However, for Yala, who participated as a speaker at EmTech Digital Latam 2018 organised by MIT Technology Review in Spanish, the next step moving forward is to work with these same models of artificial intelligence to design personalised drugs. “In this way, we can attack each cancer differently and effectively and enhance treatments for each person” he concludes.

 

 

 

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