Research Article

Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels

Volume: 79 Number: 3 September 30, 2026
Murat Zaimoğlu , Ömer Mert Özpişkin *, Cevher Şamil Doğrusöz , Emin Karakis , Melike Soylemez , Ozge Irem Dusgun , Sukran Simya Ozdere , Assoc. Prof. Beyza Doğanay Erdoğan , Yusuf Şükrü Çağlar
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Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels

Abstract

Background: Artificial intelligence (AI) is a rapidly growing sector and its impact on healthcare is obvious. Many healthcare professionals are using AI in a daily basis. Aim: The authors aimed to evaluate the evolving attitudes, active usage rates, and familiarity regarding artificial intelligence (AI) among healthcare professionals and medical students across career seniority levels, and to analyze perceptions regarding AI's future impact on medical specialties. Methods: A cross-sectional survey study was conducted between October and December 2024 at our hospital. A total of 386 validated responses from medical students, interns, residents, specialists, and professors were analyzed. Data were gathered via a 14-item structured questionnaire covering demographic characteristics, active AI adoption, subjective familiarity, and attitudes toward clinical integration. Statistical evaluations were performed using IBM SPSS v.30 (Chi-square and One-Way ANOVA, p < 0.05). Results: Active AI utilization was significantly higher among medical students compared to medical doctors (53.6% vs. 36.9%, p = 0.001). Specialties perceived to be most affected by AI were data-intensive diagnostic fields: Radiology (74.9%), Nuclear Medicine (55.7%), Medical Pathology (53.9%), and Medical Genetics (53.6%). Conversely, communication- and human-centric fields were expected to be least affected: Psychiatry (13.5%), Child and Adolescent Psychiatry (13.7%), and Pediatrics (19.2%). While 67.6% of participants supported frequent or mandatory AI integration in diagnostic testing and imaging, 57.8% explicitly opposed fully autonomous surgical procedures performed by AI. Conclusion: Healthcare providers demonstrate selective trust in AI, enthusiastically endorsing its role as a diagnostic support tool while firmly rejecting autonomous interventional clinical practice. The generational divide in active technology adoption highlights the urgent need to integrate structured AI literacy, ethical oversight, and practical training into undergraduate and postgraduate medical education curricula.

Keywords

Artificial Intelligence, Medical Specialties, Seniority, Health Personnel Attitudes, Medical Education, Diagnostic Imaging.

References

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Details

Primary Language

English

Subjects

Clinical Sciences (Other)

Journal Section

Research Article

Authors

Emin Karakis This is me
0009-0007-5987-510X
Türkiye

Melike Soylemez This is me
0009-0003-2613-5369
Türkiye

Sukran Simya Ozdere This is me
0009-0006-1173-2399
Türkiye

Publication Date

September 30, 2026

Submission Date

August 6, 2026

Acceptance Date

August 27, 2026

Published in Issue

Year 2026 Volume: 79 Number: 3

DOI

https://doi.org/10.65092/autfm.2008057

IZ

https://izlik.org/JA63GY82RK

Cite

RIS / Bibtex
APA
Zaimoğlu, M., Özpişkin, Ö. M., Doğrusöz, C. Ş., Karakis, E., Soylemez, M., Dusgun, O. I., Ozdere, S. S., Doğanay Erdoğan, A. P. B., & Çağlar, Y. Ş. (2026). Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels. Ankara Üniversitesi Tıp Fakültesi Mecmuası, 79(3), 347-354. https://doi.org/10.65092/autfm.2008057
AMA
1.Zaimoğlu M, Özpişkin ÖM, Doğrusöz CŞ, et al. Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels. Ankara Üniversitesi Tıp Fakültesi Mecmuası. 2026;79(3):347-354. doi:10.65092/autfm.2008057
Chicago
Zaimoğlu, Murat, Ömer Mert Özpişkin, Cevher Şamil Doğrusöz, et al. 2026. “Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels”. Ankara Üniversitesi Tıp Fakültesi Mecmuası 79 (3): 347-54. https://doi.org/10.65092/autfm.2008057.
EndNote
Zaimoğlu M, Özpişkin ÖM, Doğrusöz CŞ, Karakis E, Soylemez M, Dusgun OI, Ozdere SS, Doğanay Erdoğan APB, Çağlar YŞ (September 1, 2026) Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels. Ankara Üniversitesi Tıp Fakültesi Mecmuası 79 3 347–354.
IEEE
[1]M. Zaimoğlu et al., “Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels”, Ankara Üniversitesi Tıp Fakültesi Mecmuası, vol. 79, no. 3, pp. 347–354, Sept. 2026, doi: 10.65092/autfm.2008057.
ISNAD
Zaimoğlu, Murat - Özpişkin, Ömer Mert - Doğrusöz, Cevher Şamil - Karakis, Emin - Soylemez, Melike - Dusgun, Ozge Irem - Ozdere, Sukran Simya - Doğanay Erdoğan, Assoc. Prof. Beyza - Çağlar, Yusuf Şükrü. “Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels”. Ankara Üniversitesi Tıp Fakültesi Mecmuası 79/3 (September 1, 2026): 347-354. https://doi.org/10.65092/autfm.2008057.
JAMA
1.Zaimoğlu M, Özpişkin ÖM, Doğrusöz CŞ, Karakis E, Soylemez M, Dusgun OI, Ozdere SS, Doğanay Erdoğan APB, Çağlar YŞ. Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels. Ankara Üniversitesi Tıp Fakültesi Mecmuası. 2026;79:347–354.
MLA
Zaimoğlu, Murat, et al. “Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels”. Ankara Üniversitesi Tıp Fakültesi Mecmuası, vol. 79, no. 3, Sept. 2026, pp. 347-54, doi:10.65092/autfm.2008057.
Vancouver
1.Murat Zaimoğlu, Ömer Mert Özpişkin, Cevher Şamil Doğrusöz, Emin Karakis, Melike Soylemez, Ozge Irem Dusgun, Sukran Simya Ozdere, Assoc. Prof. Beyza Doğanay Erdoğan, Yusuf Şükrü Çağlar. Evolving Attitudes Toward Artificial Intelligence in Medicine: A Cross-Sectional Survey Across Career Seniority Levels. Ankara Üniversitesi Tıp Fakültesi Mecmuası. 2026 Sep. 1;79(3):347-54. doi:10.65092/autfm.2008057