AI News, Diagnostic imaging computers outperform human counterparts

Diagnostic imaging computers outperform human counterparts

But Madabhushi -- even as he gladly touts three recent examples of apparent cyber superiority played out in his lab -- also dismisses any implication of a coming future when such machines replace pathologists and radiologists.

'There's initially always going to be some wincing and anxiety among pathologists and radiologists over this idea -- that our computational imaging technology can outperform us or even take our jobs,' said Madabhushi, whose center has made significant diagnostic advances in cardiovascular disease and also brain, lung, breast, prostate and head and neck cancers since opening in 2012.

Since 2016, Madabhushi and his team have received over $9.5 million from the National Cancer Institute to develop computational tools for analysis of digital pathology images of breast, lung and head and neck cancers to identify which patients with these diseases could be spared aggressive radiotherapy or chemotherapy.

Madabhushi and co-investigators -- supported by a $608,000 U.S. Department of Defense, Congressionally Directed Medical Research Program grant -- show that while human radiologists could flag up to half of all nodules that show up in a CAT scan as 'suspicious' or 'indeterminate,' about 98 percent of those nodules actually turn out to be benign.

In a recent study published in the Journal of Medical Imaging, Madabhushi and his group showed that their computational imaging technique was between 5-8 percent superior compared to two human experts in distinguishing benign from malignant lung nodules on CAT scans.

The precise difference here is that the diagnostic imaging computers at the CCIPD can read, log, compare and contrast literally hundreds of slides of tissue samples in the amount of time a pathologist might spend on a single slide.

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