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

AI Helps Physicians Better Assess the Ef…

In a small but multi-institutional study, an artificial intelligence (AI)-based system improved providers' assessments of whether patients with bladder cancer had complete response to chemotherapy before a radical cystectomy (bladder...

Smartwatches and Fitness Bands Reveal In…

A new digital health study by researchers at Scripps Research shows how data from wearable sensors, such as smartwatches and fitness bands, can track a person’s physiological response to the...

AI may Detect Earliest Signs of Pancreat…

An artificial intelligence (AI) tool developed by Cedars-Sinai investigators accurately predicted who would develop pancreatic cancer based on what their CT scan images looked like years prior to being diagnosed...

Open Call U4H-2022-PJ2: Call for Proposa…

The Ukraine crisis has an unprecedented impact on the mental health of the displaced people in the EU coming from Ukraine. The conflict and experiences of people in war zones...

AI Reduces Miss Rate of Precancerous Pol…

Artificial intelligence reduced by twofold the rate at which precancerous polyps were missed in colorectal cancer screening, reported a team of international researchers led by Mayo Clinic. The study is...

Medical Valley EMN & Volitan Global …

The two healthcare innovation experts Medical Valley EMN and Volitan Global strengthen their existing inbound- and outbound activities through a strategic partnership. The aim is to offer companies access to...

DMEA - Connecting Digital Health Opens w…

26 - 28 April 2022, Berlin, Germany. What plans does the new federal government have concerning the digital transformation of the healthcare sector? What are the initial experiences of doctors regarding...

AI can Predict Probability of COVID-19 v…

Testing shortages, long waits for results, and an over-taxed health care system have made headlines throughout the COVID-19 pandemic. These issues can be further exacerbated in small or rural communities...

Using AI to Detect Cancer from Patient D…

A new way of using artificial intelligence to predict cancer from patient data without putting personal information at risk has been developed by a team including University of Leeds medical...

Oulu University Hospital Expands Partner…

Siemens Healthineers and Oulu University Hospital in Finland have entered a strategic partnership for the next ten years, adding to an existing radiotherapy collaboration to jointly expand and modernize the...

Positive Conclusion to DMEA - Connecting…

26 - 28 April 2022, Berlin, Germany. After three days DMEA, Europe's leading digital health event, came to a successful conclusion - with around 11,000 visitors, more than 500 exhibitors and...

AI-Enabled ECGs may Identify Patients at…

Atrial fibrillation, the most common cardiac rhythm abnormality, has been linked to one-third of ischemic strokes, the most common type of stroke. But atrial fibrillation is underdiagnosed, partly because many...