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YAPAY ZEKÂ DESTEKLİ HASTANE YÖNETİMİ VE LİDERLİĞİ: BİBLİYOMETRİK BİR ANALİZ

Yıl 2025, Cilt: 9 Sayı: 17, 83 - 111, 31.12.2025
https://doi.org/10.62666/eujmr.1826710

Öz

Günümüzde yapay zekâ (YZ) hastane yönetimi ve liderliği süreçlerinde stratejik bir dönüştürücü güç hâline gelmiştir. Bu çalışmanın amacı, 2015-2025 yılları arasında YZ destekli hastane yönetimi ve liderliği alanındaki bilimsel üretimi sistematik biçimde incelemektir. Çalışma alana ilişkin tematik eğilimlerin belirlenmesinde stratejik yol gösterici olarak özgün bir değere sahiptir. Çalışmada nicel bibliyometrik analiz yaklaşımı benimsenmiştir. Veriler 10 Kasım 2025 tarihinde Web of Science veri tabanından elde edilmiştir. Yayın türü (makale ve derleme), zaman aralığı (2015-2025) ve dil kriteri (İngilizce) filtrelemesi ile veri ön işleme (CR normalizasyonu) uygulanmıştır. Analiz, performans analizi ve bilimsel haritalama analizi olarak iki ana eksende yürütülmüştür. Analizler, RStudio (v4.5.2) ve Bibliometrix R paketi web arayüzü olan Biblioshiny (v5.0) kullanılarak gerçekleştirilmiştir. Alana ilişkin 6.394 kayıt tespit edilmiş yapılan filtreleme ve normalizasyon işlemlerinin ardından 4.669 kayıt analize dâhil edilmiştir. 2015-2025 yılları arasında yayın sayısı yaklaşık 74 kat artmıştır. Literatür büyük ölçüde Asya ve Amerika merkezli araştırma grupları tarafından şekillendirilmektedir. “machine learning”, “deep learning”, “prognostics and health management” ve “anomaly detection” teknik temalarının yönetim ve liderlik literatürüyle bütünleştiği görülmektedir. En fazla katkı yapan ülkeler Çin, ABD ve İran olurken araştırmaların odak noktası; veri odaklı karar verme, öngörücü yönetim ve dijital liderlik alanlarıdır. YZ, hastane yönetiminde stratejik yönetişim ve liderlik süreçlerini yeniden şekillendirmektedir. Literatür teknik uygulamalardan yönetimsel modellere doğru genişlemektedir. Çalışma, YZ destekli hastane yönetimi ve liderliğine ilişkin boşlukları görünür kılmakta ve gelecekteki araştırmalara yön verecek kavramsal bir çerçeve sunmaktadır.

Kaynakça

  • Ahmed, M. S., Zhinuk, F. A., Acharjee, S., Begum, S., Jobiullah, M. I., & Islam, S. (2025). Ai-driven predictive operations management: a business science framework for dynamic hospital resource optimization and clinical workflow efficiency. International Journal of Professional Business Review: Int. J. Prof. Bus. Rev., 10(8), 5.
  • Alamoodi, A. H., Zaidan, B. B., Albahri, O. S., Garfan, S., Ahmaro, I. Y., Mohammed, R. T., ... & Malik, R. Q. (2023). Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions. Complex & Intelligent Systems, 9(4), 4705-4731.
  • Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
  • Bhagat, S. V., & Kanyal, D. (2024). Navigating the future: the transformative impact of artificial intelligence on hospital management-a comprehensive review. Cureus, 16(2).
  • Boyacı, H., & Söyük, S. (2025). Healthcare workers' readiness for artificial intelligence and organizational change: a quantitative study in a university hospital. BMC Health Services Research, 25(1), 813.
  • Bulut, C. (2025). Sağlık Kurumlarında Yapay Zekâ Destekli Karar Destek Sistemlerinin Kullanımı. Uluslararası Sağlık Yönetimi ve Stratejileri Araştırma Dergisi, 11(1), 27-37.
  • Clarivate. (2025). Web of Science Core Collection. Available online: https://www.webofscience.com/wos/woscc/basic-search (accessed on 10 November 2025).
  • Çetin, V., & Yıldız, O. (2022). A comprehensive review on data preprocessing techniques in data analysis. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 28(2), 299-312.
  • D'Ascenzo, F., Rocchi, A., Iandolo, F., & Vito, P. (2024). Evolutionary impacts of artificial intelligence in Healthcare Managerial Literature. A ten-year Bibliometric and Topic Modeling Review. Sustainable Futures, 7, 100198.
  • Dicuonzo, G., Donofrio, F., Fusco, A., & Shini, M. (2023). Healthcare system: Moving forward with artificial intelligence. Technovation, 120, 102510.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296.
  • Durusoy, O. (2025). Artificial Intelligence's Expanding Role in Healthcare Administration: A Technological Revolution or a Risky Disruption?. Technium Soc. Sci. J., 73, 460.
  • García, R. E. G. (2025). Thematic evolution of research on hospital management: A longitudinal study based on Scopus. Iberoamerican Journal of Science Measurement and Communication, 5(4), 1-11.
  • Ghorbani, B. D. (2024). Bibliometrix: Science mapping analysis with R Biblioshiny based on Web of Science in applied linguistics. In A Scientometrics Research Perspective in Applied Linguistics (pp. 197-234). Cham: Springer Nature Switzerland.
  • Hamilton, A. J., Strauss, A. T., Martinez, D. A., Hinson, J. S., Levin, S., Lin, G., & Klein, E. Y. (2021). Machine learning and artificial intelligence: applications in healthcare epidemiology. Antimicrobial Stewardship & Healthcare Epidemiology, 1(1), e28.
  • Haque, A. (2025). Responsible artificial intelligence (AI) in healthcare: a paradigm shift in leadership and strategic management. Leadership in Health Services, 38(4), 644-656.
  • Hendrickson, A. B., Gilkey, K. C., Stickler, N., & Taylor, T. (2025). Evolving Healthcare Leadership in the Age of AI: A Narrative Review of Current Expected Transitions of Leadership in the era of Artificial Intelligence. International Journal of Scientific and Management Research, 8(8), 17-29.
  • Hong, N., Liu, C., Gao, J., Han, L., Chang, F., Gong, M., & Su, L. (2022). State of the art of machine learning–enabled clinical decision support in intensive care units: literature review. JMIR Medical Informatics, 10(3), e28781.
  • Hussain, W., Mabrok, M., Gao, H., Rabhi, F. A., & Rashed, E. A. (2024). Revolutionising healthcare with artificial intelligence: A bibliometric analysis of 40 years of progress in health systems. Digital Health, 10, 20552076241258757.
  • Jimma, B. L. (2023). Artificial intelligence in healthcare: A bibliometric analysis. Telematics and Informatics Reports, 9, 100041.
  • Joshi, S. (2025). Leadership in the age of AI: Review of quantitative models and visualization for managerial decision-making. Available at SSRN 5223882.
  • Kalal, N., Bishnoi, A. K., Sharma, S. K., & Deora, S. Artificial Intelligence Supported Patient Care In Cardiovascular Diseases: A Paradigm Shift From Conventional To Digital. International Journal of Environmental Sciences, 11(7), 2025.
  • Kashani, M., & Dastani, M. (2025). Evolution of artificial intelligence in medical sciences: a comprehensive scientometrics analysis. Global Knowledge, Memory and Communication.
  • K-Synth Srl. (2025). Bibliometrix (Version 5.0) [Software]. https://www.bibliometrix.org/home/ (accessed on 10 November 2025).
  • Kwon, H., An, S., Lee, H. Y., Cha, W. C., Kim, S., Cho, M., & Kong, H. J. (2022). Review of smart hospital services in real healthcare environments. Healthcare Informatics Research, 28(1), 3-15.
  • Mhlanga, D. (2025). AI in Hospital Administration: Revolutionizing Healthcare. CRC Press.
  • Na, L., Carballo, K. V., Pauphilet, J., Haddad-Sisakht, A., Kombert, D., Boisjoli-Langlois, M., ... & Bertsimas, D. (2023). Patient outcome predictions improve operations at a large hospital network. arXiv preprint arXiv:2305.15629.
  • Nianga, Z. W. (2024). Leveraging AI for Strategic Management in Healthcare: Enhancing Operational and Financial Performance. Journal of Intelligence and Knowledge Engineering (ISSN: 2959-0620), 2(3), 1.
  • Ongala, M., Kiraka, R., Choudrie, J., & Okello, J. (2025, August). Strategic Integration of Artificial Intelligence in Healthcare: Theoretical Frameworks, Adoption, Enablers, and Barriers—A Scoping Review. In Proceedings of the AAAI Symposium Series (Vol. 6, No. 1, pp. 298-303).
  • Osunlaja, O., Enahoro, A., Maha, C. C., Kolawole, T. O., & Abdul, S. (2024). Healthcare management education and training: Preparing the next generation of leaders-a review. International Journal of Applied Research in Social Sciences, 6(6), 1178-1192.
  • Owhonda, K. C. (2024). Enhancing healthcare outcomes via agile IT project management, secure data governance, and informatics-driven workflow optimization. Int J Eng Technol Res Manag, 8(12), 423.
  • Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of Managerial Science, 18(11), 3333-3361.
  • Passas, I. (2024). Bibliometric analysis: the main steps. Encyclopedia, 4(2).
  • Paterson, E., Chari, S., McCormack, L., & Sanderson, P. (2024). Application of a human factors systems approach to healthcare control centres for managing patient flow: A scoping review. Journal of Medical Systems, 48(1), 62.
  • Pelletier, P., Geuna, A., & Souza, D. (2024). Artificial intelligence research in Canadian hospitals: The development of metropolitan competencies. In Healthcare Management Forum (Vol. 37, No. 6, pp. 445-450). Sage CA: Los Angeles, CA: SAGE Publications.
  • Posit Team. (2025). RStudio: Integrated development environment for R (Version 2025.09.2+418) [Computer software]. https://posit.co/
  • Qin, H., Cai, X., Yuan, W., Huang, C., & Luo, S. (2023). Scientific knowledge production and artificial intelligence for healthcare: a scientometric view. Proceedings of the Association for Information Science and Technology, 60(1), 1104-1106.
  • Schmallenbach, L., Bärnighausen, T. W., & Lerchenmueller, M. J. (2024). The global geography of artificial intelligence in life science research. Nature Communications, 15(1), 7527.
  • Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21(1), 125.
  • Shah, B. (2024). Artificial Intelligence (AI) in Public Health and Healthcare Systems Management. Open Access Public Health and Health Administration Review, 3(1).
  • Smithson, R., Doherty, T., & Fisher, A. (2024). Managing patient flow across an acute tertiary care hospital through a centralised coordination hub: Technological and cultural change-a case study. Asia Pacific Journal of Health Management, 19(1), 180-183.
  • Sriharan, A., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: scoping review. Journal of Medical Internet Research, 26, e54556.
  • Stefanis, C., Stavropoulou, E., Stavropoulos, A., Gyriki, D., Nikolaidis, C. G., Vassos, V., ... & Bezirtzoglou, E. (2025). Innovative methodological pillars for bibliometric studies: AI screening, data normalization and dual-tool analysis. Discover Applied Sciences, 7(9), 973.
  • Tanniru, M., Khuntia, J., & Weiner, J. (2018). Hospital leadership in support of digital transformation. Pacific Asia Journal of the Association for Information Systems, 10(3), 1.
  • Tsekouropoulos, G., Vasileiou, A., Hoxha, G., Theocharis, D., Theodoridou, E., & Grigoriadis, T. (2025). Leadership 4.0: Navigating the Challenges of the Digital Transformation in Healthcare and Beyond. Administrative Sciences, 15(6), 194.
  • Tungushpayev, M., Suleimenova, D., Sarria-Santamerra, A., Aimyshev, T., Gaipov, A., & Viderman, D. (2025). The value of machine and deep learning in management of critically ill patients: An umbrella review. International Journal of Medical Informatics, 106081.
  • Turgay, Ö. F., & Özçelik, Ö. F. (2023). Data-driven approaches to hospital capacity planning and management. Inf. Knowl. Manage., 4(2), 6-14.
  • Xie, Y., Zhai, Y., & Lu, G. (2025). Evolution of artificial intelligence in healthcare: a 30-year bibliometric study. Frontiers in Medicine, 11, 1505692.
  • Zhang, L., Lin, J., Liu, B., Zhang, Z., Yan, X., & Wei, M. (2019). A review on deep learning applications in prognostics and health management. Ieee Access, 7, 162415-162438.
  • Ziadlou, D. (2021). Strategies during digital transformation to make progress in achievement of sustainable development by 2030. Leadership in Health Services, 34(4), 375-391.

ARTIFICIAL INTELLIGENCE-ENHANCED HOSPITAL MANAGEMENT AND LEADERSHIP: A BIBLIOMETRIC ANALYSIS

Yıl 2025, Cilt: 9 Sayı: 17, 83 - 111, 31.12.2025
https://doi.org/10.62666/eujmr.1826710

Öz

In the current era, artificial intelligence (AI) has become a strategic transformative force in hospital management and leadership processes. The aim of this study is to systematically examine scientific production in the field of AI-enhanced hospital management and leadership between 2015-2025. The study has unique value as a strategic guide in identifying thematic trends in the field. A quantitative bibliometric analysis approach was adopted in the study. Data were obtained from the Web of Science database on November 10, 2025. Data preprocessing (CR normalization) was applied by filtering publication type (article and review), time period (2015-2025), and language criterion (English). The analysis was conducted along two main axes: performance analysis and scientific mapping analysis. Analyses were performed using RStudio (v4.5.2) and Biblioshiny (v5.0), the web interface of the Bibliometrix R package. 6,394 records related to the field were identified and after the filtering and normalization processes, 4,669 records were included in the analysis. The number of publications increased approximately 74-fold between 2015-2025. The literature is largely shaped by research groups based in Asia and the Americas. The technical themes of “machine learning”, “deep learning”, “prognostics and health management” and “anomaly detection” appear to be integrated with management and leadership literature. While the countries that contributed the most were China, the USA and Iran, the focus of the research is on data-driven decision-making, predictive management and digital leadership. AI is reshaping strategic governance and leadership processes in hospital management. The literature is expanding from technical applications to managerial models. The study highlights gaps in AI-enabled hospital management and leadership and provides a conceptual framework to guide future research.

Kaynakça

  • Ahmed, M. S., Zhinuk, F. A., Acharjee, S., Begum, S., Jobiullah, M. I., & Islam, S. (2025). Ai-driven predictive operations management: a business science framework for dynamic hospital resource optimization and clinical workflow efficiency. International Journal of Professional Business Review: Int. J. Prof. Bus. Rev., 10(8), 5.
  • Alamoodi, A. H., Zaidan, B. B., Albahri, O. S., Garfan, S., Ahmaro, I. Y., Mohammed, R. T., ... & Malik, R. Q. (2023). Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions. Complex & Intelligent Systems, 9(4), 4705-4731.
  • Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
  • Bhagat, S. V., & Kanyal, D. (2024). Navigating the future: the transformative impact of artificial intelligence on hospital management-a comprehensive review. Cureus, 16(2).
  • Boyacı, H., & Söyük, S. (2025). Healthcare workers' readiness for artificial intelligence and organizational change: a quantitative study in a university hospital. BMC Health Services Research, 25(1), 813.
  • Bulut, C. (2025). Sağlık Kurumlarında Yapay Zekâ Destekli Karar Destek Sistemlerinin Kullanımı. Uluslararası Sağlık Yönetimi ve Stratejileri Araştırma Dergisi, 11(1), 27-37.
  • Clarivate. (2025). Web of Science Core Collection. Available online: https://www.webofscience.com/wos/woscc/basic-search (accessed on 10 November 2025).
  • Çetin, V., & Yıldız, O. (2022). A comprehensive review on data preprocessing techniques in data analysis. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 28(2), 299-312.
  • D'Ascenzo, F., Rocchi, A., Iandolo, F., & Vito, P. (2024). Evolutionary impacts of artificial intelligence in Healthcare Managerial Literature. A ten-year Bibliometric and Topic Modeling Review. Sustainable Futures, 7, 100198.
  • Dicuonzo, G., Donofrio, F., Fusco, A., & Shini, M. (2023). Healthcare system: Moving forward with artificial intelligence. Technovation, 120, 102510.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296.
  • Durusoy, O. (2025). Artificial Intelligence's Expanding Role in Healthcare Administration: A Technological Revolution or a Risky Disruption?. Technium Soc. Sci. J., 73, 460.
  • García, R. E. G. (2025). Thematic evolution of research on hospital management: A longitudinal study based on Scopus. Iberoamerican Journal of Science Measurement and Communication, 5(4), 1-11.
  • Ghorbani, B. D. (2024). Bibliometrix: Science mapping analysis with R Biblioshiny based on Web of Science in applied linguistics. In A Scientometrics Research Perspective in Applied Linguistics (pp. 197-234). Cham: Springer Nature Switzerland.
  • Hamilton, A. J., Strauss, A. T., Martinez, D. A., Hinson, J. S., Levin, S., Lin, G., & Klein, E. Y. (2021). Machine learning and artificial intelligence: applications in healthcare epidemiology. Antimicrobial Stewardship & Healthcare Epidemiology, 1(1), e28.
  • Haque, A. (2025). Responsible artificial intelligence (AI) in healthcare: a paradigm shift in leadership and strategic management. Leadership in Health Services, 38(4), 644-656.
  • Hendrickson, A. B., Gilkey, K. C., Stickler, N., & Taylor, T. (2025). Evolving Healthcare Leadership in the Age of AI: A Narrative Review of Current Expected Transitions of Leadership in the era of Artificial Intelligence. International Journal of Scientific and Management Research, 8(8), 17-29.
  • Hong, N., Liu, C., Gao, J., Han, L., Chang, F., Gong, M., & Su, L. (2022). State of the art of machine learning–enabled clinical decision support in intensive care units: literature review. JMIR Medical Informatics, 10(3), e28781.
  • Hussain, W., Mabrok, M., Gao, H., Rabhi, F. A., & Rashed, E. A. (2024). Revolutionising healthcare with artificial intelligence: A bibliometric analysis of 40 years of progress in health systems. Digital Health, 10, 20552076241258757.
  • Jimma, B. L. (2023). Artificial intelligence in healthcare: A bibliometric analysis. Telematics and Informatics Reports, 9, 100041.
  • Joshi, S. (2025). Leadership in the age of AI: Review of quantitative models and visualization for managerial decision-making. Available at SSRN 5223882.
  • Kalal, N., Bishnoi, A. K., Sharma, S. K., & Deora, S. Artificial Intelligence Supported Patient Care In Cardiovascular Diseases: A Paradigm Shift From Conventional To Digital. International Journal of Environmental Sciences, 11(7), 2025.
  • Kashani, M., & Dastani, M. (2025). Evolution of artificial intelligence in medical sciences: a comprehensive scientometrics analysis. Global Knowledge, Memory and Communication.
  • K-Synth Srl. (2025). Bibliometrix (Version 5.0) [Software]. https://www.bibliometrix.org/home/ (accessed on 10 November 2025).
  • Kwon, H., An, S., Lee, H. Y., Cha, W. C., Kim, S., Cho, M., & Kong, H. J. (2022). Review of smart hospital services in real healthcare environments. Healthcare Informatics Research, 28(1), 3-15.
  • Mhlanga, D. (2025). AI in Hospital Administration: Revolutionizing Healthcare. CRC Press.
  • Na, L., Carballo, K. V., Pauphilet, J., Haddad-Sisakht, A., Kombert, D., Boisjoli-Langlois, M., ... & Bertsimas, D. (2023). Patient outcome predictions improve operations at a large hospital network. arXiv preprint arXiv:2305.15629.
  • Nianga, Z. W. (2024). Leveraging AI for Strategic Management in Healthcare: Enhancing Operational and Financial Performance. Journal of Intelligence and Knowledge Engineering (ISSN: 2959-0620), 2(3), 1.
  • Ongala, M., Kiraka, R., Choudrie, J., & Okello, J. (2025, August). Strategic Integration of Artificial Intelligence in Healthcare: Theoretical Frameworks, Adoption, Enablers, and Barriers—A Scoping Review. In Proceedings of the AAAI Symposium Series (Vol. 6, No. 1, pp. 298-303).
  • Osunlaja, O., Enahoro, A., Maha, C. C., Kolawole, T. O., & Abdul, S. (2024). Healthcare management education and training: Preparing the next generation of leaders-a review. International Journal of Applied Research in Social Sciences, 6(6), 1178-1192.
  • Owhonda, K. C. (2024). Enhancing healthcare outcomes via agile IT project management, secure data governance, and informatics-driven workflow optimization. Int J Eng Technol Res Manag, 8(12), 423.
  • Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of Managerial Science, 18(11), 3333-3361.
  • Passas, I. (2024). Bibliometric analysis: the main steps. Encyclopedia, 4(2).
  • Paterson, E., Chari, S., McCormack, L., & Sanderson, P. (2024). Application of a human factors systems approach to healthcare control centres for managing patient flow: A scoping review. Journal of Medical Systems, 48(1), 62.
  • Pelletier, P., Geuna, A., & Souza, D. (2024). Artificial intelligence research in Canadian hospitals: The development of metropolitan competencies. In Healthcare Management Forum (Vol. 37, No. 6, pp. 445-450). Sage CA: Los Angeles, CA: SAGE Publications.
  • Posit Team. (2025). RStudio: Integrated development environment for R (Version 2025.09.2+418) [Computer software]. https://posit.co/
  • Qin, H., Cai, X., Yuan, W., Huang, C., & Luo, S. (2023). Scientific knowledge production and artificial intelligence for healthcare: a scientometric view. Proceedings of the Association for Information Science and Technology, 60(1), 1104-1106.
  • Schmallenbach, L., Bärnighausen, T. W., & Lerchenmueller, M. J. (2024). The global geography of artificial intelligence in life science research. Nature Communications, 15(1), 7527.
  • Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21(1), 125.
  • Shah, B. (2024). Artificial Intelligence (AI) in Public Health and Healthcare Systems Management. Open Access Public Health and Health Administration Review, 3(1).
  • Smithson, R., Doherty, T., & Fisher, A. (2024). Managing patient flow across an acute tertiary care hospital through a centralised coordination hub: Technological and cultural change-a case study. Asia Pacific Journal of Health Management, 19(1), 180-183.
  • Sriharan, A., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: scoping review. Journal of Medical Internet Research, 26, e54556.
  • Stefanis, C., Stavropoulou, E., Stavropoulos, A., Gyriki, D., Nikolaidis, C. G., Vassos, V., ... & Bezirtzoglou, E. (2025). Innovative methodological pillars for bibliometric studies: AI screening, data normalization and dual-tool analysis. Discover Applied Sciences, 7(9), 973.
  • Tanniru, M., Khuntia, J., & Weiner, J. (2018). Hospital leadership in support of digital transformation. Pacific Asia Journal of the Association for Information Systems, 10(3), 1.
  • Tsekouropoulos, G., Vasileiou, A., Hoxha, G., Theocharis, D., Theodoridou, E., & Grigoriadis, T. (2025). Leadership 4.0: Navigating the Challenges of the Digital Transformation in Healthcare and Beyond. Administrative Sciences, 15(6), 194.
  • Tungushpayev, M., Suleimenova, D., Sarria-Santamerra, A., Aimyshev, T., Gaipov, A., & Viderman, D. (2025). The value of machine and deep learning in management of critically ill patients: An umbrella review. International Journal of Medical Informatics, 106081.
  • Turgay, Ö. F., & Özçelik, Ö. F. (2023). Data-driven approaches to hospital capacity planning and management. Inf. Knowl. Manage., 4(2), 6-14.
  • Xie, Y., Zhai, Y., & Lu, G. (2025). Evolution of artificial intelligence in healthcare: a 30-year bibliometric study. Frontiers in Medicine, 11, 1505692.
  • Zhang, L., Lin, J., Liu, B., Zhang, Z., Yan, X., & Wei, M. (2019). A review on deep learning applications in prognostics and health management. Ieee Access, 7, 162415-162438.
  • Ziadlou, D. (2021). Strategies during digital transformation to make progress in achievement of sustainable development by 2030. Leadership in Health Services, 34(4), 375-391.
Toplam 50 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Bilgi Sistemleri Organizasyonu ve Yönetimi, Sağlıkta Bilgi İşleme
Bölüm Araştırma Makalesi
Yazarlar

Ersin Kocaman 0000-0002-3825-1548

Gönderilme Tarihi 19 Kasım 2025
Kabul Tarihi 25 Aralık 2025
Yayımlanma Tarihi 31 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 17

Kaynak Göster

APA Kocaman, E. (2025). YAPAY ZEKÂ DESTEKLİ HASTANE YÖNETİMİ VE LİDERLİĞİ: BİBLİYOMETRİK BİR ANALİZ. EUropean Journal of Managerial Research (EUJMR), 9(17), 83-111. https://doi.org/10.62666/eujmr.1826710

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