Researchers use "big data" analytics to predict triple-negative breast cancer and oth
Researchers at Case Western Reserve University and colleagues used "big data" analytics to predict if a patient is suffering from aggressive triple-negative breast cancer, slower-moving cancers or non-cancerous lesions with 95 percent accuracy.
Re: Researchers use "big data" analytics to predict triple-negative breast cancer and
AussieGirl, KristinSchwick - any thoughts about this?
Quote:
After scanning biopsy and tumor resection slides from 160 patients into a computer, the researchers found they could use nuclei of the cancerous cells to characterize and measure cell distribution and clustering patterns.
They found where the nuclei of cells had reverted to a more primitive form, a condition called anaplasia, the cells were tightly clustered and the patient suffered recurrent cancer. They graphed the nuclei in each of the images and found there was little to no overlap between the highly clustered recurrent cancer and the comparatively disperse treatable form.
The results, if confirmed through further studies, could lead to milder treatment for patients who have the non-recurrent cancer and more aggressive treatment for those with recurrent cancer, the researchers say.
"Personalized medicine is possible using this," Madabhushi said. "Using biopsy specimens, pathologists can't tell one from the other, but big data analytics can."
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