Sept. 11, 2024
PROVIDENCE, R.I. — In a cavernous converted chapel at Brown University, physician and data scientist Leo Celi observed from the sidelines as a tableful of high school students passed around a plastic, crocodilian device. The pulse oximeter clamped down on one student’s fingertip: Ninety-seven, he read out loud, before handing it off to the student next to him.
“We as doctors get a bit unhappy when you’re below 90, 92,” said physician Jack Gallifant, who recently finished a postdoc at the MIT Laboratory for Computational Physiology where Celi directs clinical research.
There was a broader point to this demonstration. Celi travels the globe coaching students and medical trainees to design artificial intelligence algorithms that predict patients’ futures — their likelihood of recovering from an illness, say, or falling ill in the first place. That work depends on reliable data, and pulse oximeters are notorious for a troubling feature: They deliver less accurate blood-oxygen readings for patients with darker skin tones.
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