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Google's Lung Cancer Detection AI Outperforms 6 Human Radiologists

Tuesday May 21, 2019. 09:00 AM , from Slashdot
Google AI researchers working with Northwestern Medicine created an AI model capable of detecting lung cancer from screening tests better than human radiologists with an average of eight years experience. VentureBeat reports: When analyzing a single CT scan, the model detected cancer 5% more often on average than a group of six human experts and was 11% more likely to reduce false positives. Humans and AI achieved similar results when radiologists were able to view prior CT scans. When it came to predicting the risk of cancer two years after a screening, the model was able to find cancer 9.5% more often compared to estimated radiologist performance laid out in the National Lung Screening Test (NLST) study.

Detailed in research published today in Nature Medicine, the end-to-end deep learning model was used to predict whether a patient has lung cancer, generating a patient lung cancer malignancy risk score and identifying the location of the malignant tissue in the lungs. The model will be made available through the Google Cloud Healthcare API as Google continues trials and additional tests with partner organizations. The model was trained using more than 42,000 chest CT screening images taken from nearly 15,000 patients, 578 of whom developed cancer within a year, during a low-dose computed tomography LDCT study the National Institutes of Health (NIH) conducted in 2002. Results were then validated with data sets from Northwestern Medicine.

Read more of this story at Slashdot.
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