Abstract
Giriş: Yapay zekâ (YZ) ve makine öğrenimi (MÖ), tıbbi uygulamalarda geniş bir kullanım alanı bulmaktadır. Bu teknolojilerin, yenilikçi hizmetler sunarken tıp eğitimine de entegre edilmesi giderek önem kazanmaktadır. Bu çalışma, tıp fakültesi öğrencilerinin YZ’ ye yönelik bilgi düzeylerini, tutumlarını ve YZ’ nin tıp eğitimindeki rolüne ilişkin yaklaşımlarını değerlendirmeyi amaçlamaktadır.
Gereç ve Yöntem: Kesitsel tipteki çalışmamızda, araştırmacılar tarafından literatür taranarak oluşturulmuş anket katılımcılara online olarak uygulandı. Anket formunun ilk bölümünde demografik veriler ile birlikte katılımcıların internet kullanım alışkanlıkları ve gündelik hayattaki yapay zekâ uygulamaları kullanımları ikinci bölümde ise tıpta YZ hakkındaki bilgi, düşünce ve yaklaşımları sorgulandı. Veriler SPSS 24.0 istatistik paket programında analiz edildi.
Bulgular: 578 katılımcının %85,3’ü YZ uygulamalarına yönelik eğitim almak istediğini belirtmiştir. Katılımcıların %68,7’si YZ’nin tıpta devrim yaratacağını düşünürken, yalnızca %19,4’ü hekimlerin yerini alabileceğine inanmaktadır. YZ’nin en çok sağlığın geliştirilmesi (%86,2) ve patoloji (%78,4) alanlarında etkili olabileceği ifade edilmiştir. Ancak %37,7’si YZ hakkında bilgi sahibi olmadığını belirtmiştir.
Tartışma: Çalışmamızın bulguları, literatürdeki çalışmalarla büyük ölçüde uyumludur ve öğrencilerin YZ’ ye yönelik farkındalık ve bilgi ihtiyaçlarını ortaya koymaktadır. Öğrencilerin YZ’ yi anlama ve uygulama ihtiyaçlarını artırmak için YZ’nin tıp müfredatına entegrasyonunun yapılması gerektiği görülmüştür.
Sonuç: Tıp fakültelerinde YZ eğitiminin sunulması, öğrencilerin bu teknolojiyi anlaması ve klinik uygulamalarında etkin bir şekilde kullanmalarını sağlayabilir.
References
- 1. Karaca O, Çalışkan A, Demir K. Tıp Eğitiminde Yapay Zeka. In: Eğitimde Yapay Zeka Kuramdan Uygulamaya. Pegem Akademi, Ankara, 2020; pp. 346-363.
- 2. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;25(1):44-56. doi: 10.1038/s41591-018-0300-7.
- 3. Tran, B. X., Vu, G. T., Ha, G. H., Vuong, Q. H., Ho, M. T., Vuong, T. T.,et al. Global evolution of research in artificial intelligence in health and medicine: a bibliometric study. Journal of Clinical Medicine, 8(3), 360. 2019 doi: 10.3390/jcm8030360
- 4. Blease C, Kharko A, Locher C, DesRoches CM, Mandl KD. US primary care in 2029: A Delphi survey on the impact of machine learning. PLoS One. 2020 Oct;15(10). doi: 10.1371/journal.pone.0239947.
- 5. Pinto Dos Santos D, Giese D, Brodehl S, Chon SH, Staab W, Klotz N, et al. Medical students’ attitude towards artificial intelligence: A multicentre survey. Eur Radiol. 2019 Apr;29(4):1640-1646. doi: 10.1007/s00330-018-5601-1.
- 6. Sit C, Srinivasan R, Amlani A, Muthuswamy K, Azam A, Monzon L, et al. Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey. Insights Imaging. 2020;11(1):14. doi: 10.1186/s13244-019-0830-7.
- 7. Baigi SFM, Sarbaz M, Ghaddaripouri K, Ghaddaripouri M, Mousavi AS, Kimiafar K. Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Front Public Health. 2021;9:753555. doi: 10.3389/fpubh.2021.753555.
- 8. Wood CS, Thomas MR, Budd J, Mashamba-Thompson TP, Herbst K, Pillay D, et al. Taking connected mobile-health diagnostics of infectious diseases to the field. Nature. 2019 Feb;566(7745):467-474. doi: 10.1038/s41586-019-0956-2.
- 9. Cho A, Johnson M, McCurry S. Artificial intelligence in medical education: A literature review. Med Teach. 2022 Jul;44(7):761-768. doi: 10.1080/0142159X.2021.1975911.
- 10. Öcal EE, Atay E, Önsüz MF, Altın F, Çokyiğit FK, Kılınç S, Köse ÖS, Yiğit FN. Tıp fakültesi öğrencilerinin tıpta yapay zeka ile ilgili düşünceleri. Türk Tıp Öğrencileri Araştırma Dergisi. 2020;2(1):9-16.
- 11. Machleid F, Kaczmarczyk R, Johann D, Balciunas J, Atzeni G, von Maltzahn F, et al. Perceptions of digital health education among European medical students: Mixed methods survey. JMIR Med Educ. 2020 Jun;6(2). doi: 10.2196/16627.
- 12. Blacketer C, Parnis R, Franke KB, Wagner M, Wang D, Tan Y, et al. Medical student knowledge and critical appraisal of machine learning: A multicentre international cross-sectional study. Intern Med J. 2021 Sep;51(9):1542-1549. doi: 10.1111/imj.15479.
- 13. Al Saad MM, Shehadeh A, Alanazi S, Alenezi M, Abu Alez A, Eid H, et al. Medical students' knowledge and attitudes toward artificial intelligence in medicine: An online survey. BMC Med Educ. 2022 Jun;22(1):327. doi: 10.1186/s12909-022-03420-x.
- 14. Stewart J, Lu J, Gahungu N, Goudie A, Fegan PG, Bennamoun M, et al. Western Australian medical students’ attitudes towards artificial intelligence in healthcare. Med Educ Online. 2021;26(1):1930078. doi: 10.1080/10872981.2021.1930078.
- 15. Chen M, Zhang B, Cai Z, Seery S, Gonzalez MJ, Ali NM, et al. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Ann Med Surg. 2022 Apr;76:103493. doi: 10.1016/j.amsu.2022.103493 . 16. Park CJ, Yi PH, Siegel EL. Medical student perspectives on the impact of artificial intelligence on the practice of medicine. Curr Probl Diagn Radiol. 2021 May;50(3):431-436. doi: 10.1067/j.cpradiol.2020.08.005.
- 17. Miller DD, Brown EW. Artificial intelligence in medical practice: the question to the answer? Am J Med. 2018 Feb;131(2):129-133. doi: 10.1016/j.amjmed.2017.10.035.
Knowledge, Opinions, and Approaches of Medical Students Regarding Artificial Intelligence in Medicine
Abstract
Introduction: Artificial intelligence (AI) and machine learning (ML) have found extensive applications in medical practice. Integrating these technologies into medical education while providing innovative services is becoming increasingly important. This study aims to evaluate the knowledge levels, attitudes, and approaches of medical students towards AI regarding the role of AI in medical education.
Materials and Methods: In this cross-sectional descriptive study, an online survey created by the researchers based on a literature review was administered to participants. The first section of the survey included demographic data, participants' internet usage habits, and their use of AI applications in daily life. The second section assessed their knowledge, opinions, and approaches toward AI in medicine. Data were analyzed using the SPSS 24.0 statistical software.
Results: 85.3% of the 578 participants stated that they wanted to receive training on AI applications. While 68.7% believed AI would revolutionize medicine, only 19.4% thought it could replace physicians. AI was considered most effective in health promotion (86.2%) and pathology (78.4%). However, 37.7% reported having no knowledge about AI.
Discussion: The findings of this study align with the literature and highlight medical students' awareness and educational needs regarding AI. It was seen that AI should be integrated into the medical curriculum in order to increase students' understanding and application needs of AI.
Conclusion: Providing AI education in medical schools can enable students to understand this technology and use it effectively in their clinical practices.
Keywords
artificial intelligence medical education machine learning decision support systems student attitudes
References
- 1. Karaca O, Çalışkan A, Demir K. Tıp Eğitiminde Yapay Zeka. In: Eğitimde Yapay Zeka Kuramdan Uygulamaya. Pegem Akademi, Ankara, 2020; pp. 346-363.
- 2. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;25(1):44-56. doi: 10.1038/s41591-018-0300-7.
- 3. Tran, B. X., Vu, G. T., Ha, G. H., Vuong, Q. H., Ho, M. T., Vuong, T. T.,et al. Global evolution of research in artificial intelligence in health and medicine: a bibliometric study. Journal of Clinical Medicine, 8(3), 360. 2019 doi: 10.3390/jcm8030360
- 4. Blease C, Kharko A, Locher C, DesRoches CM, Mandl KD. US primary care in 2029: A Delphi survey on the impact of machine learning. PLoS One. 2020 Oct;15(10). doi: 10.1371/journal.pone.0239947.
- 5. Pinto Dos Santos D, Giese D, Brodehl S, Chon SH, Staab W, Klotz N, et al. Medical students’ attitude towards artificial intelligence: A multicentre survey. Eur Radiol. 2019 Apr;29(4):1640-1646. doi: 10.1007/s00330-018-5601-1.
- 6. Sit C, Srinivasan R, Amlani A, Muthuswamy K, Azam A, Monzon L, et al. Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey. Insights Imaging. 2020;11(1):14. doi: 10.1186/s13244-019-0830-7.
- 7. Baigi SFM, Sarbaz M, Ghaddaripouri K, Ghaddaripouri M, Mousavi AS, Kimiafar K. Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Front Public Health. 2021;9:753555. doi: 10.3389/fpubh.2021.753555.
- 8. Wood CS, Thomas MR, Budd J, Mashamba-Thompson TP, Herbst K, Pillay D, et al. Taking connected mobile-health diagnostics of infectious diseases to the field. Nature. 2019 Feb;566(7745):467-474. doi: 10.1038/s41586-019-0956-2.
- 9. Cho A, Johnson M, McCurry S. Artificial intelligence in medical education: A literature review. Med Teach. 2022 Jul;44(7):761-768. doi: 10.1080/0142159X.2021.1975911.
- 10. Öcal EE, Atay E, Önsüz MF, Altın F, Çokyiğit FK, Kılınç S, Köse ÖS, Yiğit FN. Tıp fakültesi öğrencilerinin tıpta yapay zeka ile ilgili düşünceleri. Türk Tıp Öğrencileri Araştırma Dergisi. 2020;2(1):9-16.
- 11. Machleid F, Kaczmarczyk R, Johann D, Balciunas J, Atzeni G, von Maltzahn F, et al. Perceptions of digital health education among European medical students: Mixed methods survey. JMIR Med Educ. 2020 Jun;6(2). doi: 10.2196/16627.
- 12. Blacketer C, Parnis R, Franke KB, Wagner M, Wang D, Tan Y, et al. Medical student knowledge and critical appraisal of machine learning: A multicentre international cross-sectional study. Intern Med J. 2021 Sep;51(9):1542-1549. doi: 10.1111/imj.15479.
- 13. Al Saad MM, Shehadeh A, Alanazi S, Alenezi M, Abu Alez A, Eid H, et al. Medical students' knowledge and attitudes toward artificial intelligence in medicine: An online survey. BMC Med Educ. 2022 Jun;22(1):327. doi: 10.1186/s12909-022-03420-x.
- 14. Stewart J, Lu J, Gahungu N, Goudie A, Fegan PG, Bennamoun M, et al. Western Australian medical students’ attitudes towards artificial intelligence in healthcare. Med Educ Online. 2021;26(1):1930078. doi: 10.1080/10872981.2021.1930078.
- 15. Chen M, Zhang B, Cai Z, Seery S, Gonzalez MJ, Ali NM, et al. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Ann Med Surg. 2022 Apr;76:103493. doi: 10.1016/j.amsu.2022.103493 . 16. Park CJ, Yi PH, Siegel EL. Medical student perspectives on the impact of artificial intelligence on the practice of medicine. Curr Probl Diagn Radiol. 2021 May;50(3):431-436. doi: 10.1067/j.cpradiol.2020.08.005.
- 17. Miller DD, Brown EW. Artificial intelligence in medical practice: the question to the answer? Am J Med. 2018 Feb;131(2):129-133. doi: 10.1016/j.amjmed.2017.10.035.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Clinical Sciences (Other) |
| Journal Section | Research Article |
| Authors | |
| Publication Date | April 30, 2025 |
| Submission Date | November 23, 2024 |
| Acceptance Date | March 20, 2025 |
| Published in Issue | Year 2025 Volume: 5 Issue: 1 |
