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.
Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology / M. Codari, L. Melazzini, S.P. Morozov, C.C. van Kuijk, L.M. Sconfienza, F. Sardanelli. - In: INSIGHTS INTO IMAGING. - ISSN 1869-4101. - 10:1(2019 Dec).
|Titolo:||Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology|
CODARI, MARINA (Corresponding)
|Parole Chiave:||Artificial Intelligence; Machine Learning; Radiologists; Radiology; Surveys and Questionnaires|
|Settore Scientifico Disciplinare:||Settore MED/36 - Diagnostica per Immagini e Radioterapia|
|Data di pubblicazione:||dic-2019|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1186/s13244-019-0798-3|
|Appare nelle tipologie:||01 - Articolo su periodico|