Skip to Navigation Skip to Search Skip to Content
Search All Centers

Can Artificial Intelligence Predict Lung Cancer Outcomes?

Can Artificial Intelligence Predict Lung Cancer Outcomes?
View next

Published on May 18, 2020

One of the many exciting advances in scientific research is the use of artificial intelligence (AI), also called deep learning, to help predict how cancer patients will respond to certain treatments. Wouldn’t it be great to know ahead of time, with evidence-based data, how you will do, or if you are likely to experience toxic side effects? With AI, that may be possible.

What Is Artificial Intelligence?

AI is the development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition and decision-making.

Using algorithms and historical data, these computer systems make predictions by analyzing information from multiple sources and recognizing data patterns. This emerging field is full of possibilities.

Man Versus Machine

At the recent annual meeting of the American Association for Cancer Research (AACR), a new study was announced about the use of computed tomography (CT) scans as predictive tools. Researchers used CT scans in patients diagnosed with advanced non-small cell lung cancer (NSCLC), and AI-trained algorithms to predict tumor sensitivity to three systemic cancer therapies.

The purpose of this study was to predict tumor sensitivity to nivolumab (Opdivo), docetaxel (Taxotere) and gefitinib (Iressa). The aim is to produce better outcomes for patients with NSCLC by determining which drug or combination of drugs is likely to be most effective.

Last year’s annual meeting of the American Society of Clinical Oncology (ASCO) also revealed some exciting news about artificial intelligence as a potential game-changer for patients.

“I think the focus is not as much on new drugs that we're coming out with but learning more information about the drugs we know and also learning about how to predict and select out patients so we can maximize their benefit,” said Dr. Nicholas Rohs, a leading lung cancer expert from Mount Sinai Health System.

At the end of this month, ASCO presenters, patients, and patient advocates will gather online for the ASCO20 Virtual Scientific Program to accelerate learning about how the field is moving forward and what patients can expect at their next doctor’s visit.

Ask Questions

During your next routine visits, ask members of your team how they are using AI in their testing or development of treatment plans, and how that might affect how decisions are made for your treatment plan. Harnessing the power of big data sets will, ideally, lead to better patient outcomes.

~Lauren Evoy Davis


Please remember the opinions expressed on Patient Power are not necessarily the views of our sponsors, contributors, partners or Patient Power. Our discussions are not a substitute for seeking medical advice or care from your own doctor. That’s how you’ll get care that’s most appropriate for you.

Recommended for You

References

  1. Dercle L, et al. Identification of Non–Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics. Clin Cancer Research. March 20, 2020

Featuring

View next