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Role of artificial intelligence in the care of patients with nonsmall cell lung cancer
Author(s) -
Rabbani Mohamad,
Kanevsky Jonathan,
Kafi Kamran,
Chandelier Florent,
Giles Francis J.
Publication year - 2018
Publication title -
european journal of clinical investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.164
H-Index - 107
eISSN - 1365-2362
pISSN - 0014-2972
DOI - 10.1111/eci.12901
Subject(s) - lung cancer , medicine , narrative review , intensive care medicine , personalized medicine , health care , cancer , precision medicine , artificial intelligence , medical physics , oncology , pathology , bioinformatics , computer science , economics , biology , economic growth
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,” “machine learning,” “lung cancer,” “Nonsmall Cell Lung Cancer ( NSCLC ),” “diagnosis” 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 throughout 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.