The Massachusetts Institute of Technology's (MIT) Imaging Group is studying the use of magnetic resonance imaging (MRI) technology to identify chemical compounds from their spectrographic signatures instead of imaging.
Although this method requires the development of new analytic techniques, it could help medical researchers determine how the brain's chemistry changes during the progress of different neurological diseases.
MIT professor Polina Golland is investigating the functional characterization of the brain, using functional MRIs and diffusion MRIs. Golland helped develop a computer-modeling system that can explain the progression of several neurological diseases that appear to start in one region of the brain and then move outward to others.
Other researchers have used electrocardiogram readings and machine learning to identify correlations between medical-sensor data and disease.
The researchers created algorithms to analyze electrocardiogram data, and found three previously unknown indicators of the likelihood of a heart attack.
Other MIT researchers are studying the automatic recognition of epileptic seizures using data from scalp-worm electroencephalogram sensors. The researchers are using machine learning to calibrate their seizure-detection algorithms to individual patients.
From MIT News
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