AI Tool Predicts Colon Cancer Survival, Treatment Response
Model offers actionable insights for physicians, could augment clinical decisions in resource-limited areas
Model offers actionable insights for physicians, could augment clinical decisions in resource-limited areas
At a glance:
A new artificial intelligence model designed by researchers at Harvard Medical School and National Cheng Kung University in Taiwan could bring much-needed clarity to doctors delivering prognoses and deciding on treatments for patients with colorectal cancer, the second deadliest cancer worldwide.
Solely by looking at images of tumor samples — microscopic depictions of cancer cells — the new tool accurately predicts how aggressive a colorectal tumor is, how likely the patient is to survive with and without disease recurrence, and what the optimal therapy might be for them.
Having a tool that answers such questions could help clinicians and patients navigate this wily disease, which often behaves differently even among people with similar disease profiles who receive the same treatment — and could ultimately spare some of the 1 million lives that colorectal cancer claims every year.
A report on the team’s work is published in Nature Communications.
The researchers say that the tool is meant to enhance, not replace, human expertise.
“Our model performs tasks that human pathologists cannot do based on image viewing alone,” said study co-senior author Kun-Hsing Yu, assistant professor of biomedical informatics in the Blavatnik Institute at HMS. Yu led an international team of pathologists, oncologists, biomedical informaticians, and computer scientists.
Also see
Harvard Team Uses Bridges-2 to Build AI Cancer Diagnosis Tool | Pittsburgh Supercomputing Center
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