Artificial intelligence as a diagnostic tool for lung nodule evaluation

Abstract

The clinical evaluation of lung nodules begins with an assessment of the probability that the nodule is malignant. The probability of malignancy can be estimated based on clinical experience or by using validated prediction models that incorporate known clinical and radiographic features associated with lung cancer. There has been a growing interest in the use of artificial intelligence (AI) to aid clinicians in performing this task. Advances in machine learning techniques have fostered progress in the development of automated systems with the goal to match or exceed the performance of clinicians. In this article we will review how lung nodules are currently evaluated, how AI may be used in lung nodule detection and classification, discuss its limitations, future directions and the necessary steps for its application in clinical practice.