
Researchers developed MAGIC, an AI-based system integrating automated microscopy and genomics to study chromosomal abnormalities linked to cancer.
Key Details
- 1MAGIC uses automated microscopy, AI-driven image analysis, and single-cell genome sequencing to identify and tag abnormal cells.
- 2The system can analyse nearly 100,000 cells in less than a day, vastly exceeding manual methods.
- 3Chromosomal abnormalities were seen in just over 10% of cell divisions, doubling with mutated p53 gene.
- 4MAGIC relies on a laser and photoconvertible dye to mark target cells, facilitating further analysis.
- 5The tool is versatile and can be trained to identify a variety of visually distinct cellular features.
Why It Matters

Source
EurekAlert
Related News

UVA's $4M NIH Grant Backs AI to Optimize Cardiac MRI Therapies
UVA secures $4 million NIH funding to develop GenStrain, an AI model using MRI data to personalize cardiac pacing therapies.

Machine Learning Models Predict Cancer Risk with Routine Health Data
Researchers developed machine learning models using routinely collected health data to predict individual risk for 20 common cancers, outperforming traditional methods for several cancer types.

Duke Receives $25M to Lead National Trustworthy AI Hub for Dementia and Aging
Duke University has launched a $25 million national center to make AI for aging and dementia clinically robust and trustworthy.