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For: Ongena YP, Haan M, Yakar D, Kwee TC. Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire. Eur Radiol 2020;30:1033-40. [PMID: 31705254 DOI: 10.1007/s00330-019-06486-0] [Cited by in Crossref: 42] [Cited by in F6Publishing: 34] [Article Influence: 10.5] [Reference Citation Analysis]
Number Citing Articles
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7 Alloulbi A, Öz T, Alzubi A, Goel N. The Use of Artificial Intelligence for Smart Decision-Making in Smart Cities: A Moderated Mediated Model of Technology Anxiety and Internal Threats of IoT. Mathematical Problems in Engineering 2022;2022:1-12. [DOI: 10.1155/2022/6707431] [Reference Citation Analysis]
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11 Rakovic K, Colling R, Browning L, Dolton M, Horton MR, Protheroe A, Lamb AD, Bryant RJ, Scheffer R, Crofts J, Stanislaus E, Verrill C. The Use of Digital Pathology and Artificial Intelligence in Histopathological Diagnostic Assessment of Prostate Cancer: A Survey of Prostate Cancer UK Supporters. Diagnostics 2022;12:1225. [DOI: 10.3390/diagnostics12051225] [Reference Citation Analysis]
12 Yan X, Yan J, Chen H. Design and Implementation of Interactive Platform for Operation and Maintenance of Multimedia Information System Based on Artificial Intelligence and Big Data. Computational Intelligence and Neuroscience 2022;2022:1-9. [DOI: 10.1155/2022/4620930] [Reference Citation Analysis]
13 Tian L, Zhang Z, Long Y, Tang A, Deng M, Long X, Fang N, Yu X, Ruan X, Qiu J, Wang X, Deng H. Endoscopists' Acceptance on the Implementation of Artificial Intelligence in Gastrointestinal Endoscopy: Development and Case Analysis of a Scale. Front Med (Lausanne) 2022;9:760634. [PMID: 35492311 DOI: 10.3389/fmed.2022.760634] [Reference Citation Analysis]
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15 Patel B, Makaryus AN. Reply to Giansanti, D. Comment on “Patel, B.; Makaryus, A.N. Artificial Intelligence Advances in the World of Cardiovascular Imaging. Healthcare 2022, 10, 154”. Healthcare 2022;10:735. [DOI: 10.3390/healthcare10040735] [Reference Citation Analysis]
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17 Kosan E, Krois J, Wingenfeld K, Deuter CE, Gaudin R, Schwendicke F. Patients' Perspectives on Artificial Intelligence in Dentistry: A Controlled Study. J Clin Med 2022;11:2143. [PMID: 35456236 DOI: 10.3390/jcm11082143] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Giansanti D, Di Basilio F. The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus. Healthcare 2022;10:509. [DOI: 10.3390/healthcare10030509] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
19 Di Basilio F, Esposisto G, Monoscalco L, Giansanti D. The Artificial Intelligence in Digital Radiology: Part 2: Towards an Investigation of acceptance and consensus on the Insiders. Healthcare (Basel) 2022;10:153. [PMID: 35052316 DOI: 10.3390/healthcare10010153] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
20 Monoscalco L, Simeoni R, Maccioni G, Giansanti D. Information Security in Medical Robotics: A Survey on the Level of Training, Awareness and Use of the Physiotherapist. Healthcare 2022;10:159. [DOI: 10.3390/healthcare10010159] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
21 Bokhari SAA, Myeong S. Use of Artificial Intelligence in Smart Cities for Smart Decision-Making: A Social Innovation Perspective. Sustainability 2022;14:620. [DOI: 10.3390/su14020620] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 12.0] [Reference Citation Analysis]
22 Elkefi S, Layeb SB. Artificial Intelligence and Operations Research in a Middle Ground to Support Decision-Making in Healthcare Systems in Africa. Africa Case Studies in Operations Research 2022. [DOI: 10.1007/978-3-031-17008-9_3] [Reference Citation Analysis]
23 Musbahi O, Syed L, Le Feuvre P, Cobb J, Jones G. Public patient views of artificial intelligence in healthcare: A nominal group technique study. Digit Health 2021;7:20552076211063682. [PMID: 34950499 DOI: 10.1177/20552076211063682] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
24 González-Gonzalo C, Thee EF, Klaver CCW, Lee AY, Schlingemann RO, Tufail A, Verbraak F, Sánchez CI. Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice. Prog Retin Eye Res 2021;:101034. [PMID: 34902546 DOI: 10.1016/j.preteyeres.2021.101034] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
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26 Weinert L, Müller J, Svensson L, Heinze O. The perspective of IT decision makers on factors influencing adoption and implementation of AI-technologies in 40 German Hospitals: Descriptive Analysis (Preprint). JMIR Medical Informatics. [DOI: 10.2196/34678] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
27 Yakar D, Ongena YP, Kwee TC, Haan M. Do People Favor Artificial Intelligence Over Physicians? A Survey Among the General Population and Their View on Artificial Intelligence in Medicine. Value in Health 2021. [DOI: 10.1016/j.jval.2021.09.004] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
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30 Young AT, Amara D, Bhattacharya A, Wei ML. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. Lancet Digit Health 2021;3:e599-611. [PMID: 34446266 DOI: 10.1016/S2589-7500(21)00132-1] [Cited by in Crossref: 8] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
31 Aggarwal R, Farag S, Martin G, Ashrafian H, Darzi A. Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey. J Med Internet Res 2021;23:e26162. [PMID: 34236994 DOI: 10.2196/26162] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
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33 Lennox-Chhugani N, Chen Y, Pearson V, Trzcinski B, James J. Women's attitudes to the use of AI image readers: a case study from a national breast screening programme. BMJ Health Care Inform 2021;28:e100293. [PMID: 33795236 DOI: 10.1136/bmjhci-2020-100293] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
34 Botwe BO, Antwi WK, Arkoh S, Akudjedu TN. Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study. J Med Radiat Sci 2021;68:260-8. [PMID: 33586361 DOI: 10.1002/jmrs.460] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 6.0] [Reference Citation Analysis]
35 Ongena YP, Yakar D, Haan M, Kwee TC. Artificial Intelligence in Screening Mammography: A Population Survey of Women’s Preferences. Journal of the American College of Radiology 2021;18:79-86. [DOI: 10.1016/j.jacr.2020.09.042] [Cited by in Crossref: 17] [Cited by in F6Publishing: 11] [Article Influence: 8.5] [Reference Citation Analysis]
36 Kovarik CL. Patient Perspectives on the Use of Artificial Intelligence. JAMA Dermatol 2020;156:493-4. [PMID: 32159724 DOI: 10.1001/jamadermatol.2019.5013] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.7] [Reference Citation Analysis]
37 Sollini M, Bartoli F, Marciano A, Zanca R, Slart RHJA, Erba PA. Artificial intelligence and hybrid imaging: the best match for personalized medicine in oncology. Eur J Hybrid Imaging 2020;4:24. [PMID: 34191197 DOI: 10.1186/s41824-020-00094-8] [Cited by in Crossref: 13] [Cited by in F6Publishing: 13] [Article Influence: 4.3] [Reference Citation Analysis]
38 Abdoul C, Cros P, Coutier L, Hadchouel A, Neuraz A, Burgun A, Giovannini-Chami L, Drummond D. Parents' views on artificial intelligence for the daily management of childhood asthma: a survey. J Allergy Clin Immunol Pract 2021;9:1728-1730.e3. [PMID: 33290917 DOI: 10.1016/j.jaip.2020.11.048] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
39 Aggarwal R, Farag S, Martin G, Ashrafian H, Darzi A. Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey (Preprint).. [DOI: 10.2196/preprints.26162] [Reference Citation Analysis]
40 Bhandari AP, Liong R, Koppen J, Murthy SV, Lasocki A. Noninvasive Determination of IDH and 1p19q Status of Lower-grade Gliomas Using MRI Radiomics: A Systematic Review. AJNR Am J Neuroradiol 2021;42:94-101. [PMID: 33243896 DOI: 10.3174/ajnr.A6875] [Cited by in Crossref: 24] [Cited by in F6Publishing: 26] [Article Influence: 8.0] [Reference Citation Analysis]
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43 Lennartz S, Dratsch T, Zopfs D, Persigehl T, Maintz D, Große Hokamp N, Pinto dos Santos D. Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives (Preprint).. [DOI: 10.2196/preprints.24221] [Reference Citation Analysis]
44 Mccradden MD, Sarker T, Paprica PA. Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.. [DOI: 10.1101/2020.04.25.20079814] [Reference Citation Analysis]
45 Liew C, Lim CY. Our patients have spoken: keep radiologists in the centre of AI imaging ecosystems. Eur Radiol 2020;30:1031-2. [PMID: 31728690 DOI: 10.1007/s00330-019-06531-y] [Reference Citation Analysis]