The AI researchers from Google who is working with Northwestern Medicine created an AI model capable of detecting lung cancer from screening tests. It is said to be better than human radiologists with an average of eight years' experience.
When analyzing a single CT scan, the AI model was able to detect cancer 5% more often on average than a group of six human radiologists and was 11% more likely to reduce false positives. AI and humans achieved similar results when radiologists were able to view prior to the CT scans.
When it came to predicting the risk of cancer two years after the screening tests, the AI model was able to find cancer 9.5% more often compared to the radiologist performance that was laid out in the NLST study or the National Lung Screening Test.
This study was published in Nature Medicine, the deep learning model was used to predict whether a patient has lung cancer, creating a patient lung cancer malignancy-risk score and identifying the location of the malignant tissue in the patient's lungs.
The AI model will be available through the Google Cloud Healthcare API as Google continues trials and additional tests with partner organizations.
"The AI system uses 3D volumetric deep learning to analyze the full anatomy on chest CT scans, as well as patches based on object detection techniques that identify regions with malignant lesions," Google technical lead Shravya Shetty and product manager Daniel Tse said in a blog post today.
The model was trained by using more than 42,000 chest CT screening images that were taken from around 15,000 patients, 578 of whom developed lung cancer within a year during a low-dose computed tomography LDCT study that NIH or the National Institutes of Health conducted in 2002. The results were then validated by Northwestern Medicine.
Lung cancer is one of the most common causes of death, according to the World Health Organization. The cancer is taking more than 2 million lives every year and it is killing as many people each year as breast cancer. A study in 2015 showed that only 2 to 4% of patients get LDCT screenings.
"By showing that deep learning can increase specificity without sacrificing sensitivity, we hope to spur more research and conversation around the role AI can play in tipping the cost-benefit scale for cancer screening," the blog post reads.
This is Google's first foray into cancer detection and treatment.
