Role of artificial intelligence in the care of patients with
nonsmall cell lung cancer
McGill University Health Centre, McGill
University, Montreal, QC, Canada
Imagia Cybernetics, Montreal, QC,
Developmental Therapeutics Consortium,
Chicago, IL, USA
Francis J. Giles, Developmental
Therapeutics Consortium, Chicago IL,
Background: Lung cancer is the leading cause of cancer death worldwide. In up
to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival
rate ranges between 10%-16%. There has been a significant amount of research
using machine learning to generate tools using patient data to improve outcomes.
Methods: This narrative review is based on research material obtained from
PubMed up to Nov 2017. The search terms include “artificial intelligence,”“ma-
chine learning,”“lung cancer,”“Nonsmall Cell Lung Cancer (NSCLC),”“diagno-
sis” and “treatment.”
Results: Recent studies support the use of computer-aided systems and the use of
radiomic features to help diagnose lung cancer earlier. Other studies have looked
at machine learning (ML) methods that offer prognostic tools to doctors and help
them in choosing personalized treatment options for their patients based on
molecular, genetics and histological features. Combining artificial intelligence
approaches into health care may serve as a beneficial tool for patients with
NSCLC, and this review outlines these benefits and current shortcomings through-
out the continuum of care.
Conclusion: We present a review of the various applications of ML methods in
NSCLC as it relates to improving diagnosis, treatment and outcomes.
artificial intelligence, big data, deep learning, lung cancer, machine learning, NSCLC
Lung cancer remains the most frequently diagnosed cancer
and a leading cause of cancer-related mortality worldwide.
Due to late presentation of clinical symptoms and limited
screening programmes, as many as 57% of patients diag-
nosed with lung cancer present with metastasis.
cally, approximately 85% of all new lung cancer cases are
classified as nonsmall cell lung cancers (NSCLC), 10% are
small cell lung cancer (SCLC) and 5% account for other
Most NSCLC can be grouped into 3 main categories:
Squamous Cell Carcinoma, Adenocarcinoma and Large
Cell Carcinoma histo-subtypes. Besides histological, clini-
cal and demographic information, a wide range of data
ranging from genomics, proteomics, immunohistochemistry
and imaging must be integrated by physicians when devel-
oping personalized treatment plans for patients which can
be challenging and lead to unfavourable outcomes. Further-
more, there are a number of factors that limit timely access
to these tests, including high cost and late availability in
the patient care continuum.
Received: 31 December 2017
Accepted: 28 January 2018
Eur J Clin Invest. 2018;48:e12901.
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