Artificial Intelligence, Machine Learning and Radiomics in Radiology

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The use of artificial intelligence (AI) in radiology – radiomics – has been getting a lot of attention, fuelled by the availability of large datasets, substantial advances in computing power, and new deep-learning algorithms. This has led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks. Machine learning in radiology, a subset of artificial intelligence, is expected to have a substantial clinical impact, with the imaging examinations routinely obtained in clinical practice providing an opportunity to improve decision support in medical image interpretation.

On this page, we present a collection of articles showcasing recent research on these topics. Studies undertaken confirm the expectation that AI in radiology will bring significant changes. In an article in Academic Radiology, doctors at New Jersey Medical School discuss this impact and the benefits it could bring, predicting that artificial intelligence will lead to a fundamental change in practice in many professional fields. Deep learning (DL), part of a broader family of machine learning methods, has recently become a remarkably powerful tool for image processing.

The challenges and potential pitfalls to this tool are discussed in a study published in the Journal of the American College of Radiology, where it is concluded that for deep learning in radiology to succeed, appropriately annotated, large data sets are needed. A further study in Clinical Radiology looks at how a machine-learning based approach can be applied to classify chest radiographs as normal or abnormal. The anticipation of AI's role in clinical radiology has been met with anxiety about job security by some, and optimism about the potential to streamline monotonous functions by others. Irrespective of how they feel, researchers in an article published in Clinical Imaging strongly feel that radiologists should ensure they are at the forefront of this inevitable marriage of man and machine, molding AI into a powerful tool that will solidify their position as the fulcrum in clinical medicine.

You can find out more about these studies and others in our special collection on Artificial Intelligence, Machine Learning and Radiomics, which is free to access online until 31 December 2018.


Article collection

Academic Radiology

Canadian Association of Radiologists Journal

Clinical Imaging

Clinical Radiology

European Journal of Radiology

Heliyon

Journal of Forensic Radiology and Imaging

Journal of the American College of Radiology

Journal of Vascular and Interventional Radiology

Magnetic Resonance Imaging

Physica Medica