Lung cancer remains as the most common cause of cancer death in the United States, resulting in an estimated 160,000 deaths in 2018. Since 2013, low-dose computed tomography (LDCT) lung cancer screening in high-risk populations has been the recommendation though most are only diagnosed following a length of symptoms.
Recently, a team led by researchers at Google AI (Artificial Intelligence) in Mountain View, CA, has developed a deep-learning model that can predict lung malignancies. The model, a neural network trained with lung cancer CT scans, performs as well as, or better than, trained radiologists.
“This extensive deep neural net assessment represents a step forward for CT lung cancer screening in smokers, which has been plagued by very high rates of false positives and negatives,” notes Eric Topol, MD, executive vice president of Scripps Research, and founder and director, Scripps Research Translational Institute. He tells GEN that “the algorithms require prospective clinical validation, but are certainly promising.”The collaborative work is published today in Nature Medicine in a paper titled, “End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.” The guidelines set for image interpretation by radiologists are based on a variety of image findings, but primarily “nodule size, density, and growth,” note the authors. But, Lily Peng, MD, PhD, product manager at Google, notes that “very early stage cancer is miniscule and can be hard to see” adding that “over 80% of lung cancer cases are not caught early.”
One may ask, “Why would I want to use AI to replace my doctor?” The idea is not to replace, but to better aide ability. An exciting component of this technology is how early Google’s AI is able to detect the cancer in early scans. In one case, it detected a patient’s cancer on a scan taken one year before the patient was diagnosed. An author of the study said, “For patients like this, early detection could translate to an increased survival rate of 40%.”
The future is looking brighter with the benefits of technology like this, and it will constantly improve. Though we believe that early diagnosis doesn’t always equal better survival, treating cancer as soon as one can always improves outcomes. It’s exciting!
Dr. Conners graduated with his doctorate from Northwestern Health Sciences University in 1986 and has been studying alternative cancer care for over 20 years. He holds AMA Fellowships in Regenerative & Functional Medicine and Integrative Cancer Therapy.
He is the author of numerous books including, Stop Fighting Cancer and Start Treating the Cause, Cancer Can’t Kill You if You’re Already Dead, Help, My Body is Killing Me, Chronic Lyme, 3 Phases of Lyme, 23 Steps to Freedom, and many more you can download for FREE on our books page.