Versatile AI System Revolutionizes Analysis of Medical Image Series: Study Finds
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A new AI-based system for analyzing images taken over time can accurately detect changes and predict outcomes, according to a study led by investigators at Weill Cornell Medicine, Cornell’s Ithaca campus and Cornell Tech. The system’s sensitivity and flexibility could make it useful across a wide range of medical and scientific applications.
The new system, termed LILAC (Learning-based Inference of Longitudinal imAge Changes), is based on an AI approach called machine learning
In the study, the researchers developed the system and demonstrated it on diverse time-series of images—also called “longitudinal” image series—covering developing IVF embryos, healing tissue after wounds and aging brains. The researchers showed that LILAC has a broad ability to identify even very subtle differences between images taken at different times, and to predict related outcome measures such as cognitive scores from brain scans.
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