Why it’s a problem that pulse oximeters don’t work as well on patients of color
New research ties inaccuracies in pulse oximeter readings to racial disparities in treatment and outcomes.
New research ties inaccuracies in pulse oximeter readings to racial disparities in treatment and outcomes.
Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.
The technique opens a door to manufacturing of pressure-monitoring bandages, shade-shifting fabrics, or touch-sensing robots.
New stamp-sized ultrasound adhesives produce clear images of heart, lungs, and other internal organs.
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
The MIT Mobility Initiative welcomes five inaugural industry members to advance safe, clean, and inclusive mobility.
Cheap and quick to produce, these digitally manufactured plasma sensors could help scientists predict the weather or study climate change.
Neuroscience professor and Science Hub investigator Ted Adelson explains how simulating the sense of touch with a camera can make robots smarter.
Faculty members recognized for excellence via a diverse array of honors, grants, and prizes.
“Interpretability methods” seek to shed light on how machine-learning models make predictions, but researchers say to proceed with caution.
Researchers have found a material that can perform much better than silicon. The next step is finding practical and economic ways to make it.
The findings of a large-scale screen could help researchers design nanoparticles that target specific types of cancer.
MIT researchers create KineCAM, an instant camera that yields images that appear to move.
Alex Shalek’s technologies for single-cell RNA profiling can help dissect the cellular bases of complex diseases around the globe.
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.