Google’s new research shows how AI can predict lung cancer in ways that could boost the chances of survival
Google’s research team have used a deep-learning algorithm to predict lung cancer accurately from computed scans. The company have recently published their findings in the journal Nature Medicine.
Google researchers created a model that can not only generate the overall lung cancer malignancy prediction (viewed in 3D volume) but also identify subtle malignant tissue in the lungs (lung nodules).
The model can also factor in information from previous scans, useful in predicting lung cancer risk because the growth rate of suspicious lung nodules can be indicative of malignancy.
“Using advances in 3D volumetric modelling alongside datasets from our partners (including Northwestern University), we’ve made progress in modelling lung cancer prediction as well as laying the groundwork for future clinical testing,” Shravya Shetty, M.S. Technical Lead at Google wrote in a blog post.
Google leveraged 45,856 de-identified chest CT screening cases (some in which cancer was found) from NIH’s research dataset from the National Lung Screening Trial study and Northwestern University and validated the results with a second dataset and also compared their results against 6 U.S. board-certified radiologists.
The Google researchers work demonstrates the potential for AI to increase both accuracy and consistency, which could help accelerate adoption of lung cancer screening worldwide. Google says the initial results are encouraging, but further studies will assess the impact and utility in clinical practice.