Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology
Abstract We report the results of a survey conducted among ESR members in November and December 2018, asking for expectations about artificial intelligence (AI) in 5–10 years. Of 24,000 ESR members contacted, 675 (2.8%) completed the survey, 454 males (67%), 555 (82%) working at academic/public hosp...
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doaj-cd7c0bdb767c471ba007a7dd8006b0bc2020-11-25T03:56:54ZengSpringerOpenInsights into Imaging1869-41012019-10-0110111110.1186/s13244-019-0798-3Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of RadiologyEuropean Society of Radiology (ESR)Abstract We report the results of a survey conducted among ESR members in November and December 2018, asking for expectations about artificial intelligence (AI) in 5–10 years. Of 24,000 ESR members contacted, 675 (2.8%) completed the survey, 454 males (67%), 555 (82%) working at academic/public hospitals. AI impact was mostly expected (≥ 30% of responders) on breast, oncologic, thoracic, and neuro imaging, mainly involving mammography, computed tomography, and magnetic resonance. Responders foresee AI impact on: job opportunities (375/675, 56%), 218/375 (58%) expecting increase, 157/375 (42%) reduction; reporting workload (504/675, 75%), 256/504 (51%) expecting reduction, 248/504 (49%) increase; radiologist’s profile, becoming more clinical (364/675, 54%) and more subspecialised (283/675, 42%). For 374/675 responders (55%) AI-only reports would be not accepted by patients, for 79/675 (12%) accepted, for 222/675 (33%) it is too early to answer. For 275/675 responders (41%) AI will make the radiologist-patient relation more interactive, for 140/675 (21%) more impersonal, for 259/675 (38%) unchanged. If AI allows time saving, radiologists should interact more with clinicians (437/675, 65%) and/or patients (322/675, 48%). For all responders, involvement in AI-projects is welcome, with different roles: supervision (434/675, 64%), task definition (359/675, 53%), image labelling (197/675, 29%). Of 675 responders, 321 (48%) do not currently use AI, 138 (20%) use AI, 205 (30%) are planning to do it. According to 277/675 responders (41%), radiologists will take responsibility for AI outcome, while 277/675 (41%) suggest shared responsibility with other professionals. To summarise, responders showed a general favourable attitude towards AI.http://link.springer.com/article/10.1186/s13244-019-0798-3Artificial IntelligenceMachine LearningRadiologistsRadiologySurveys and Questionnaires |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
European Society of Radiology (ESR) |
spellingShingle |
European Society of Radiology (ESR) Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology Insights into Imaging Artificial Intelligence Machine Learning Radiologists Radiology Surveys and Questionnaires |
author_facet |
European Society of Radiology (ESR) |
author_sort |
European Society of Radiology (ESR) |
title |
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology |
title_short |
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology |
title_full |
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology |
title_fullStr |
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology |
title_full_unstemmed |
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology |
title_sort |
impact of artificial intelligence on radiology: a euroaim survey among members of the european society of radiology |
publisher |
SpringerOpen |
series |
Insights into Imaging |
issn |
1869-4101 |
publishDate |
2019-10-01 |
description |
Abstract We report the results of a survey conducted among ESR members in November and December 2018, asking for expectations about artificial intelligence (AI) in 5–10 years. Of 24,000 ESR members contacted, 675 (2.8%) completed the survey, 454 males (67%), 555 (82%) working at academic/public hospitals. AI impact was mostly expected (≥ 30% of responders) on breast, oncologic, thoracic, and neuro imaging, mainly involving mammography, computed tomography, and magnetic resonance. Responders foresee AI impact on: job opportunities (375/675, 56%), 218/375 (58%) expecting increase, 157/375 (42%) reduction; reporting workload (504/675, 75%), 256/504 (51%) expecting reduction, 248/504 (49%) increase; radiologist’s profile, becoming more clinical (364/675, 54%) and more subspecialised (283/675, 42%). For 374/675 responders (55%) AI-only reports would be not accepted by patients, for 79/675 (12%) accepted, for 222/675 (33%) it is too early to answer. For 275/675 responders (41%) AI will make the radiologist-patient relation more interactive, for 140/675 (21%) more impersonal, for 259/675 (38%) unchanged. If AI allows time saving, radiologists should interact more with clinicians (437/675, 65%) and/or patients (322/675, 48%). For all responders, involvement in AI-projects is welcome, with different roles: supervision (434/675, 64%), task definition (359/675, 53%), image labelling (197/675, 29%). Of 675 responders, 321 (48%) do not currently use AI, 138 (20%) use AI, 205 (30%) are planning to do it. According to 277/675 responders (41%), radiologists will take responsibility for AI outcome, while 277/675 (41%) suggest shared responsibility with other professionals. To summarise, responders showed a general favourable attitude towards AI. |
topic |
Artificial Intelligence Machine Learning Radiologists Radiology Surveys and Questionnaires |
url |
http://link.springer.com/article/10.1186/s13244-019-0798-3 |
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