Sep 17, 2018 05:54 PM
https://www.eurekalert.org/pub_releases/...091718.php
EXCERPT: A new computer program can analyze images of patients' lung tumors, specify cancer types, and even identify altered genes driving abnormal cell growth, a new study shows. Led by researchers at NYU School of Medicine and published online in Nature Medicine, the study found that a type of artificial intelligence (AI), or "machine learning" program, could distinguish with 97 percent accuracy between adenocarcinoma and squamous cell carcinoma--two lung cancer types that experienced pathologists at times struggle to parse without confirmatory tests.
The AI tool was also able to determine whether abnormal versions of 6 genes linked to lung cancer--including EGFR, KRAS, and TP53--were present in cells, with an accuracy that ranged from 73 to 86 percent depending on the gene. Such genetic changes or mutations often cause the abnormal growth seen in cancer, but can also change a cell's shape and interactions with its surroundings, providing visual clues for automated analysis....
MORE: https://www.eurekalert.org/pub_releases/...091718.php
EXCERPT: A new computer program can analyze images of patients' lung tumors, specify cancer types, and even identify altered genes driving abnormal cell growth, a new study shows. Led by researchers at NYU School of Medicine and published online in Nature Medicine, the study found that a type of artificial intelligence (AI), or "machine learning" program, could distinguish with 97 percent accuracy between adenocarcinoma and squamous cell carcinoma--two lung cancer types that experienced pathologists at times struggle to parse without confirmatory tests.
The AI tool was also able to determine whether abnormal versions of 6 genes linked to lung cancer--including EGFR, KRAS, and TP53--were present in cells, with an accuracy that ranged from 73 to 86 percent depending on the gene. Such genetic changes or mutations often cause the abnormal growth seen in cancer, but can also change a cell's shape and interactions with its surroundings, providing visual clues for automated analysis....
MORE: https://www.eurekalert.org/pub_releases/...091718.php