Researchers at the Stanford University School of Medicine have found that computers trained to detect lung cancer tissue may actually be more accurate than any human doctor. The study’s findings were published in Nature Communications.
“Pathology as it is practiced now is very subjective. Two highly skilled pathologists assessing the same slide will agree only about 60 percent of the time. This approach replaces this subjectivity with sophisticated, quantitative measurements that we feel are likely to improve patient outcomes,” said Michael Snyder, PhD, professor and chair of genetics. 
In order to train the computer to pick up lung cancer, they used 2,186 images from the Cancer Genome Atlas. Individuals whose pictures were used had been diagnosed with adenocarcinoma or squamous cell carcinoma.
Previously, doctors examined tumor tissue mounted on glass slides with a light microscope to determine the severity of the cancer. In layman’s terms, the more abnormal the tissue looks, the moreThis post was originally published on this site