Preventive health care: AI helps accessibility

In the United States, AI shows promise for helping underserved communities by supporting preventive health care.

While the commercialization of AI has grown tremendously in recent years, the healthcare industry needs to do things differently, and for good reason. “In health, we have to look at the ethics of applying technology, and we come from a mindset where whether it’s technology, whether it’s a vaccine, it has to be safe and effective before you release it,” said Belinda Seto, deputy director in the Office of Strategy. of Data Science for the National Institutes of Health (NIH).

“Artificial intelligence has been used in healthcare mostly in medical radiology,” she said. As a tool, machine learning has been useful in analyzing images to gain comprehensive insight into pattern recognition. “By default, it will also inform us when there is an abnormal pattern to what the images are showing us, and therefore, improve the detection and diagnosis of a disease.”

For Seto, understanding and deciphering patterns has long been a passion. After moving to the United States in the fifth grade, Seto’s love of science began with her fascination with Hong Kong’s local tropical flowers. In fact, the patterns and irregularities within petals and flowers fascinated him to the point of pursuing an undergraduate degree in biology.

In graduate school, Seto received her Ph.D. in biochemistry from Purdue University. “I went much deeper mechanistically, what are some of the processes that make our cells work? How do these individual biochemical processes occur?” she explained. “Basically, I studied the chemistry of proteins and enzymes.”

Her journey later took her from the Stadtman lab of the National Heart, Lung, and Blood Institute to the Federal Drug Administration and back to the NIH. “Over the course of my career, I’ve held multiple leadership positions, both in policy leadership, program leadership, and now in the data science office,” Seto said. “I felt like I was in the middle of this huge opportunity of things being experimented with, things that could be seen happening and implemented in real-life situations, but wow, all the time this technology is evolving!”

However, an evolving technological landscape requires a cultural shift. With a mission to improve the disparity in access and quality of care, Seto wants to see further health equity in the country. “There is no linear path,” she continued.

“Let’s say you have the best diagnostic test. Setting this up can be heavily based on access to that technology. Second, there are structural barriers to access; there are cultural issues about accepting that technology,” Seto explained. Spreading health and science literacy is essential, she said.