Artificial Intelligence in medical imaging practice: looking to the future.
Sarah J LewisZiba GandomkarPatrick C BrennanPublished in: Journal of medical radiation sciences (2019)
Artificial intelligence (AI) is heralded as the most disruptive technology to health services in the 21st century. Many commentary articles published in the general public and health domains recognise that medical imaging is at the forefront of these changes due to our large digital data footprint. Radiomics is transforming medical images into mineable high-dimensional data to optimise clinical decision-making; however, some would argue that AI could infiltrate workplaces with very few ethical checks and balances. In this commentary article, we describe how AI is beginning to change medical imaging services and the innovations that are on the horizon. We explore how AI and its various forms, including machine learning, will challenge the way medical imaging is delivered from workflow, image acquisition, image registration to interpretation. Diagnostic radiographers will need to learn to work alongside our 'virtual colleagues', and we argue that there are vital changes to entry and advanced curricula together with national professional capabilities to ensure machine-learning tools are used in the safest and most effective manner for our patients.
Keyphrases
- artificial intelligence
- machine learning
- deep learning
- big data
- healthcare
- high resolution
- decision making
- electronic health record
- primary care
- convolutional neural network
- newly diagnosed
- randomized controlled trial
- ejection fraction
- public health
- prognostic factors
- magnetic resonance
- lymph node metastasis
- climate change
- risk assessment
- chronic kidney disease
- health insurance
- human health
- photodynamic therapy
- fluorescence imaging