What the Radiologist should Know about Artificial Intelligence - An ESR White Paper

This paper aims to provide a review of the basis for application of AI in radiology, to discuss the immediate ethical and professional impact in radiology, and to consider possible future evolution. Even if AI does add significant value to image interpretation, there are implications outside the traditional radiology activities of lesion detection and characterisation. In radiomics, AI can foster the analysis of the features and help in the correlation with other omics data. Imaging biobanks would become a necessary infrastructure to organise and share the image data from which AI models can be trained. AI can be used as an optimising tool to assist the technologist and radiologist in choosing a personalised patient's protocol, tracking the patient's dose parameters, providing an estimate of the radiation risks. AI can also aid the reporting workflow and help the linking between words, images, and quantitative data. Finally, AI coupled with CDS can improve the decision process and there by optimise clinical and radiological workflow.

This paper was prepared by Prof. Emanuele Neri (Chair of the ESR eHealth and Informatics Subcommittee), Prof. Nandita de Souza (Chair of the ESR European Imaging Biomarkers Alliance - EIBALL Subcommittee), and Dr. Adrian Brady (Chair of the ESR Quality, Safety and Standards Committee), on behalf of and supported by the eHealth and Informatics Subcommittee of the European Society of Radiology (ESR).

The authors gratefully acknowledge the valuable contribution to the paper of Dr. Angel Alberich Bayarri, Prof. Christoph D. Becker, Dr. Francesca Coppola, and Dr. Jacob Visser, as members of the ESR eHealth and Informatics Subcommittee.

The paper was approved by the ESR Executive Council in February 2019.

Download: What the Radiologist should Know about Artificial Intelligence - An ESR White Paper (.pdf, 546 KB).

Download from eHealthNews.eu: What the Radiologist should Know about Artificial Intelligence - An ESR White Paper (.pdf, 546 KB).

Most Popular Now

Derby Starts Drive for Safer and more In…

DXC Technology (NYSE: DXC) is collaborating with Royal Derby Hospital, part of the University Hospitals of Derby and Burton NHS Foundation Trust, on an initiative that will better alert doctors...

What the Radiologist should Know about A…

This paper aims to provide a review of the basis for application of AI in radiology, to discuss the immediate ethical and professional impact in radiology, and to consider possible...

The Mobile Game that can Detect Alzheime…

A specially designed mobile phone game can detect people at risk of Alzheimer's - according to new research from the University of East Anglia. Researchers studied gaming data from an...

Hospital Diagnoses Critically Ill Childr…

The Rady Children’s Hospital (San Diego, USA) used Moon, software developed by the Leuven-based (Belgium) company Diploid. Moon is the first software worldwide to use Artificial Intelligence (AI) for the...

AstraZeneca Starts Artificial Intelligen…

AstraZeneca and BenevolentAI began a long-term collaboration to use artificial intelligence (AI) and machine learning for the discovery and development of new treatments for chronic kidney disease (CKD) and idiopathic...

Novartis Presents First-of-its-Kind Algo…

Novartis today announced results from a validation study of the innovative, algorithm-based digital solution MS Progression Discussion Tool, or MSProDiscussTM. The tool aims to support and facilitate a discussion between...

Red Hat Helps Public Health England Use …

Red Hat, Inc. (NYSE: RHT), the world's leading provider of open source solutions, announced that Public Health England (PHE), an executive agency of the Department of Health and Social Care...

Bayer Joins Sensyne Health Consortium Wo…

Sensyne Health plc (LSE: SENS), the British clinical AI technology company, and Bayer, the life sciences company, announce that Bayer has become Sensyne Health's preferred pharmaceutical partner to work together...