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Table 1 Multiple-choice questions related to respondent’s age, sex, radiology subspecialty, most frequently practiced techniques and working status, type of institution, and country

From: Impact of artificial intelligence on radiology: a EuroAIM survey among members of the European Society of Radiology

Question number

Topic

Answers

Maximum number

List

I

Status

1

Medical student, Resident, Radiologist, Engineer/Computer scientist, Physicist, Other

II

Working place

1

University/Teaching hospital, Hospital, Private practice, Private research centre, Private company, Other

III

Gender

1

Male, Female

IV

Age range

1

18–29 years; 30–39 years; 40–49 years; 50–59 years; 60–69 years; ≥ 70 years

V

Home country

1

Albania; Austria; Armenia; Belarus; Belgium; Bosnia and Herzegovina; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Georgia; Germany; Greece; Hungary; Iceland; Ireland; Israel; Italy; Kazakhstan; Kosovo; Kyrgyzstan; Latvia; Lithuania; Luxembourg; Macedonia; Malta; Montenegro; Netherlands; Norway; Poland; Portugal; Romania; Russia; Serbia; Slovakia; Slovenia; Spain; Sweden; Switzerland; Turkey; Ukraine; United Kingdom; Uzbekistan

VI

Subspecialty

5

Breast; Cardiovascular; Emergency; Gastrointestinal/Abdominal; General; Head & Neck; Interventional; Molecular imaging/Nuclear; Musculoskeletal; Neuroradiology; Oncologic imaging; Paediatric; Thoracic; Urogenital

VII

Practiced techniques

5

Radiography; Mammography; Ultrasound; Angiography/Fluoroscopy; CT; MRI; PET/Nuclear; Hybrid imaging; DXA; Experimental imaging (animal models); Optical imaging; Other