AIHealthThere’s a lot of talk about artificial intelligence, or AI, these days. AI is everywhere—from virtual assistants to facial recognition software. The technology is even assisting doctors and scientists. So what exactly is AI? And how is it helping advance scientific research?

“AI is basically trying to teach computers to ‘think’ in the same way as the human brain,” says Dr. Despina Kontos, an AI researcher at Columbia University.

One approach to AI uses a process called machine learning. In machine learning, a computer model is built to predict what may happen in the real world. The model is taught to analyze and recognize patterns in a data set. This training enables the model to then make predictions about new data. Some AI programs can also teach themselves to ask new questions and make novel connections between pieces of information.

“Computer models and humans can really work well together to improve human health,” explains Dr. Grace C.Y. Peng, an NIH expert on AI in medicine. “Computers are very good at doing calculations at a large scale, but they don’t have the intuitive capability that we have. They’re powerful, but how helpful they’re going to be lies in our hands.”

Researchers are exploring ways to harness the power of AI to improve health care. These include assisting with diagnosing and treating medical conditions and delivering care.

Mining Medical Images

One area that AI is already being used daily is medical imaging. Computers help doctors comb through CT and MRI scans for signs of problems like heart disease and cancer.

“AI can look at images very closely, in a way that’s much more detailed than we can do with the human eye,” Kontos says. That means that the computer may be able to pick up on subtleties that a person might miss.

In medicine, catching early signs of certain diseases can be the difference between life and death. Kontos and her team are testing ways AI can be used to identify women who are at high risk for developing breast cancer. They’re using AI to analyze different features in mammograms—X-ray pictures of the breast—such as breast density. Women who have a higher risk of breast cancer can take preventative steps, like more frequent screenings. This approach could help lead to earlier diagnosis and more successful treatment.

The team is also testing whether they can use AI to individualize breast cancer treatment based on imaging results that show how breast tumors are responding. AI may better reveal who needs more intensive treatment, like chemotherapy, and who can safely skip it.

“That way, we could spare women who don’t need intensive treatment from unnecessary side effects,” Kontos explains.

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