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Artificial Intelligence and Ethics in Healthcare: A Bibliometric Analysis

Year 2024, Volume: 15 Issue: 43, 1046 - 1062, 31.08.2024
https://doi.org/10.21076/vizyoner.1455659

Abstract

The rapid proliferation of artificial intelligence (AI) in healthcare services has underscored the importance of ethical considerations. This development highlights the need to examine ethical implications, debates, concerns, and thoughts from diverse and broad perspectives. In this context, the study focuses on the ethical dimensions of AI in the healthcare domain. AI is increasingly being used in various healthcare applications, but this usage brings along ethical challenges. The aim of the research is to identify themes, trends, and critical points related to AI ethics in healthcare. Through literature review and bibliometric analyses, it is observed that AI ethics research in healthcare revolves around fundamental concepts such as ethics, AI, machine learning, healthcare services, and privacy. Additionally, the leading countries, authors, and institutions in the field are examined. The intensity of collaboration and knowledge sharing in the literature is steadily increasing. In conclusion, considering the potential benefits and challenges of AI use in healthcare, addressing ethical issues, ensuring data security, and enhancing transparency in AI decision processes are crucial. The study aims to provide a deeper understanding of AI ethics topics in the existing literature and guide future research.

References

  • Ahmad, O. F., Soares, A. S., Mazomenos, E., Brandao, P., Vega, R., Seward, E., Stoyanov, D., Chand, M., & Lovat, L. B. (2019). Artificial intelligence and computer-aided diagnosis in colonoscopy: Current evidence and future directions. The lancet Gastroenterology & hepatology, 4(1), 71-80.
  • Agac, G., Sevim, F., Celik, O., Bostan, S., Erdem, R., & Yalcin, Y. I. (2023). Research hotspots, trends and opportunities on the metaverse in health education: A bibliometric analysis. Library Hi Tech, (ahead-of-print).
  • Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., & Badreldin, H. A. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1), 689.
  • Aquino, Y. S. J., Rogers, W. A., Braunack-Mayer, A., Frazer, H., Win, K. T., Houssami, N., Degeling, C., Semsarian, C., & Carter, S. M. (2023). Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills. International Journal of Medical Informatics, 169, 104903.
  • Ardila, D., Kiraly, A. P., Bharadwaj, S., Choi, B., Reicher, J. J., Peng, L., Tse, D., Etemadi, M., Ye, W., & Corrado, G. (2019). End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature medicine, 25(6), 954-961.
  • Aydın, E., & Ersoy, N. (1995). Tıp etiği ilkeleri. Türkiye Klinikleri Tıbbi Etik Ankara-1995.
  • Bellini, V., Guzzon, M., Bigliardi, B., Mordonini, M., Filippelli, S., & Bignami, E. (2020). Artificial intelligence: a new tool in operating room management. Role of machine learning models in operating room optimization. Journal of medical systems, 44(1), 20.
  • Celik, E., Durmus, A., Adizel, O., & Nergiz Uyar, H. (2021). A bibliometric analysis: What do we know about metals (loids) accumulation in wild birds? Environmental Science and Pollution Research, 28, 10302-10334.
  • Chuang, C.-W., Chang, A., Chen, M., Selvamani, M. J. P., & Shia, B.-C. (2022). A Worldwide Bibliometric Analysis of Publications on Artificial Intelligence and Ethics in the Past Seven Decades. Sustainability, 14(18), 11125.
  • Cresswell, K., Rigby, M., Magrabi, F., Scott, P., Brender, J., Craven, C. K., Wong, Z. S.-Y., Kukhareva, P., Ammenwerth, E., & Georgiou, A. (2023). The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision. Health policy, 136, 104889.
  • Dias, R., & Torkamani, A. (2019). Artificial intelligence in clinical and genomic diagnostics. Genome medicine, 11(1), 1-12.
  • Erdemir, A. D. (2005). Etik, Tıp Etiği, Tep Etiği İlkeleri Ve Hasta Hekim İlişkilerinde Etiğin Yeri. Erdem, 15(44), 27-72.
  • Feathers, T. (2021). Google’s new dermatology app wasn’t designed for people with darker skin. Retrieved August, 10, 2022.
  • Fournier-Tombs, E., & McHardy, J. (2023). A medical ethics framework for conversational artificial intelligence. Journal of Medical Internet Research, 25, e43068.
  • Freitas, A. T. (2023). Data-Driven Approaches in Healthcare: Challenges and Emerging Trends. Multidisciplinary Perspectives on Artificial Intelligence and the Law, 65-80.
  • Gutierrez, G. (2020). Artificial intelligence in the intensive care unit. Annual Update in Intensive Care and Emergency Medicine 2020, 667-681.
  • Güzel, Ş., Dömbekci, H. A., & Fettah, E. (2022). Yapay zekânın sağlık alanında kullanımı: Nitel bir araştırma. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 9(4), 509-519.
  • Hamdoun, S., Monteleone, R., Bookman, T., & Michael, K. (2023). AI-based and digital mental health apps: Balancing need and risk. IEEE Technology and Society Magazine, 42(1), 25-36.
  • Herington, J., McCradden, M. D., Creel, K., Boellaard, R., Jones, E. C., Jha, A. K., Rahmim, A., Scott, P. J., Sunderland, J. J., & Wahl, R. L. (2023). Ethical considerations for artificial intelligence in medical imaging: deployment and governance. Journal of Nuclear Medicine, 64(10), 1509-1515.
  • Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399.
  • Kehl, K. L., Xu, W., Gusev, A., Bakouny, Z., Choueiri, T. K., Riaz, I. B., Elmarakeby, H., Van Allen, E. M., & Schrag, D. (2021). Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset. Nature communications, 12(1), 7304.
  • Khogali, H. O., & Mekid, S. (2023). The blended future of automation and AI: Examining some long-term societal and ethical impact features. Technology in Society, 73, 102232.
  • Kulak, M., Ozkan, A., & Bindak, R. (2019). A bibliometric analysis of the essential oil-bearing plants exposed to the water stress: How long way we have come and how much further? Scientia horticulturae, 246, 418-436.
  • Laçin, D., & Alparslan, E. (2024). Yapay zekâ ve tip etiği: Yapay zekâyi tip alaninda kullanmak ne kadar doğru? Evrim Ağacı.
  • McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., Back, T., Chesus, M., Corrado, G. S., & Darzi, A. (2020). International evaluation of an AI system for breast cancer screening. nature, 577(7788), 89-94.
  • Miner, A. S., Laranjo, L., & Kocaballi, A. B. (2020). Chatbots in the fight against the COVID-19 pandemic. NPJ digital medicine, 3(1), 65.
  • Oliveira, A. L. (2019). Biotechnology, big data and artificial intelligence. Biotechnology journal, 14(8), 1800613.
  • Polat, C., Sağlam, M., & Tuğba, S. (2013). Atatürk üniversitesi iktisadi ve idari bilimler dergisi’nin bibliyometrik analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(2), 273-288.
  • Shah, W. S., Elkhwesky, Z., Jasim, K. M., Elkhwesky, E. F. Y., & Elkhwesky, F. F. Y. (2023). Artificial intelligence in healthcare services: past, present and future research directions. Review of Managerial Science, 1-23.
  • Sihlahla, I., Donnelly, D. L., Townsend, B., & Thaldar, D. (2023). Legal and ethical principles governing the use of artificial intelligence in radiology services in South Africa. Developing World Bioethics.
  • Small, H. (2003). Paradigms, citations, and maps of science: A personal history. Journal of the American Society for information Science and Technology, 54(5), 394-399.
  • Sun, J., Wang, M.-H., & Ho, Y.-S. (2012). A historical review and bibliometric analysis of research on estuary pollution. Marine Pollution Bulletin, 64(1), 13-21.
  • Van Der Niet, A. G., & Bleakley, A. (2021). Where medical education meets artificial intelligence:‘Does technology care?’. Medical Education, 55(1), 30-36.
  • Zhang, J., & Zhang, Z.-M. (2023). Ethics and governance of trustworthy medical artificial intelligence. BMC Medical Informatics and Decision Making, 23(1), 7.
  • Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222, 106994.

Sağlık Hizmetlerinde Yapay Zeka ve Etik: Bir Bibliyometrik Analiz

Year 2024, Volume: 15 Issue: 43, 1046 - 1062, 31.08.2024
https://doi.org/10.21076/vizyoner.1455659

Abstract

Sağlık hizmetlerinde yapay zekanın hızla yaygınlaşması, etik ilgili tartışma, kaygı, düşüncelerin önemini farklı ve geniş bir perspektifte değerlendirmesini gerekli kılmaktadır. Bu gelişme, sağlık alanında yapay zeka uygulamalarının artan etkisini ve beraberinde getirdiği etik sorunları daha yakından inceleme gerekliliğini ortaya koymaktadır. Bu bağlamda tasarlanan bu çalışma, sağlık alanındaki YZ’nin etik boyutlarına odaklanmaktadır. YZ, sağlık alanında çeşitli uygulamalarda kullanılmakta ve bu kullanım etik zorluklarını beraberinde getirmektedir. Araştırmanın amacı ise sağlık alanındaki YZ etiği ile ilgili temaları, eğilimleri ve önemli noktaları belirlemektir. Literatür incelemesi ve bibliyometrik analizler sayesinde, sağlık alanındaki YZ etiği araştırmalarının etik, YZ, makine öğrenimi, sağlık hizmetleri ve mahremiyet gibi temel kavramlar etrafında büyüdüğü görülmektedir. Ayrıca, bu alanda öncü rol oynayan ülke, yazar ve kurumların analizi yapılmıştır. Literatürdeki işbirliği ve bilgi paylaşımının yoğunluğu giderek artığı gözlemlenmiştir. Sonuç olarak, sağlık alanındaki yapay zeka kullanımının potansiyel faydaları ve karşılaşılan zorluklar göz önüne alındığında, etik meselelerin, veri güvenliğinin ve yapay zeka karar süreçlerinin şeffaflığının ele alınması gerekmektedir. Bu çalışma, mevcut literatürdeki yapay zeka etiği konularında daha derinlemesine anlayış sağlamak ve gelecekteki araştırmalara yol göstermek amacıyla yapılmıştır.

References

  • Ahmad, O. F., Soares, A. S., Mazomenos, E., Brandao, P., Vega, R., Seward, E., Stoyanov, D., Chand, M., & Lovat, L. B. (2019). Artificial intelligence and computer-aided diagnosis in colonoscopy: Current evidence and future directions. The lancet Gastroenterology & hepatology, 4(1), 71-80.
  • Agac, G., Sevim, F., Celik, O., Bostan, S., Erdem, R., & Yalcin, Y. I. (2023). Research hotspots, trends and opportunities on the metaverse in health education: A bibliometric analysis. Library Hi Tech, (ahead-of-print).
  • Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., & Badreldin, H. A. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1), 689.
  • Aquino, Y. S. J., Rogers, W. A., Braunack-Mayer, A., Frazer, H., Win, K. T., Houssami, N., Degeling, C., Semsarian, C., & Carter, S. M. (2023). Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills. International Journal of Medical Informatics, 169, 104903.
  • Ardila, D., Kiraly, A. P., Bharadwaj, S., Choi, B., Reicher, J. J., Peng, L., Tse, D., Etemadi, M., Ye, W., & Corrado, G. (2019). End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature medicine, 25(6), 954-961.
  • Aydın, E., & Ersoy, N. (1995). Tıp etiği ilkeleri. Türkiye Klinikleri Tıbbi Etik Ankara-1995.
  • Bellini, V., Guzzon, M., Bigliardi, B., Mordonini, M., Filippelli, S., & Bignami, E. (2020). Artificial intelligence: a new tool in operating room management. Role of machine learning models in operating room optimization. Journal of medical systems, 44(1), 20.
  • Celik, E., Durmus, A., Adizel, O., & Nergiz Uyar, H. (2021). A bibliometric analysis: What do we know about metals (loids) accumulation in wild birds? Environmental Science and Pollution Research, 28, 10302-10334.
  • Chuang, C.-W., Chang, A., Chen, M., Selvamani, M. J. P., & Shia, B.-C. (2022). A Worldwide Bibliometric Analysis of Publications on Artificial Intelligence and Ethics in the Past Seven Decades. Sustainability, 14(18), 11125.
  • Cresswell, K., Rigby, M., Magrabi, F., Scott, P., Brender, J., Craven, C. K., Wong, Z. S.-Y., Kukhareva, P., Ammenwerth, E., & Georgiou, A. (2023). The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision. Health policy, 136, 104889.
  • Dias, R., & Torkamani, A. (2019). Artificial intelligence in clinical and genomic diagnostics. Genome medicine, 11(1), 1-12.
  • Erdemir, A. D. (2005). Etik, Tıp Etiği, Tep Etiği İlkeleri Ve Hasta Hekim İlişkilerinde Etiğin Yeri. Erdem, 15(44), 27-72.
  • Feathers, T. (2021). Google’s new dermatology app wasn’t designed for people with darker skin. Retrieved August, 10, 2022.
  • Fournier-Tombs, E., & McHardy, J. (2023). A medical ethics framework for conversational artificial intelligence. Journal of Medical Internet Research, 25, e43068.
  • Freitas, A. T. (2023). Data-Driven Approaches in Healthcare: Challenges and Emerging Trends. Multidisciplinary Perspectives on Artificial Intelligence and the Law, 65-80.
  • Gutierrez, G. (2020). Artificial intelligence in the intensive care unit. Annual Update in Intensive Care and Emergency Medicine 2020, 667-681.
  • Güzel, Ş., Dömbekci, H. A., & Fettah, E. (2022). Yapay zekânın sağlık alanında kullanımı: Nitel bir araştırma. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 9(4), 509-519.
  • Hamdoun, S., Monteleone, R., Bookman, T., & Michael, K. (2023). AI-based and digital mental health apps: Balancing need and risk. IEEE Technology and Society Magazine, 42(1), 25-36.
  • Herington, J., McCradden, M. D., Creel, K., Boellaard, R., Jones, E. C., Jha, A. K., Rahmim, A., Scott, P. J., Sunderland, J. J., & Wahl, R. L. (2023). Ethical considerations for artificial intelligence in medical imaging: deployment and governance. Journal of Nuclear Medicine, 64(10), 1509-1515.
  • Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399.
  • Kehl, K. L., Xu, W., Gusev, A., Bakouny, Z., Choueiri, T. K., Riaz, I. B., Elmarakeby, H., Van Allen, E. M., & Schrag, D. (2021). Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset. Nature communications, 12(1), 7304.
  • Khogali, H. O., & Mekid, S. (2023). The blended future of automation and AI: Examining some long-term societal and ethical impact features. Technology in Society, 73, 102232.
  • Kulak, M., Ozkan, A., & Bindak, R. (2019). A bibliometric analysis of the essential oil-bearing plants exposed to the water stress: How long way we have come and how much further? Scientia horticulturae, 246, 418-436.
  • Laçin, D., & Alparslan, E. (2024). Yapay zekâ ve tip etiği: Yapay zekâyi tip alaninda kullanmak ne kadar doğru? Evrim Ağacı.
  • McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., Back, T., Chesus, M., Corrado, G. S., & Darzi, A. (2020). International evaluation of an AI system for breast cancer screening. nature, 577(7788), 89-94.
  • Miner, A. S., Laranjo, L., & Kocaballi, A. B. (2020). Chatbots in the fight against the COVID-19 pandemic. NPJ digital medicine, 3(1), 65.
  • Oliveira, A. L. (2019). Biotechnology, big data and artificial intelligence. Biotechnology journal, 14(8), 1800613.
  • Polat, C., Sağlam, M., & Tuğba, S. (2013). Atatürk üniversitesi iktisadi ve idari bilimler dergisi’nin bibliyometrik analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 27(2), 273-288.
  • Shah, W. S., Elkhwesky, Z., Jasim, K. M., Elkhwesky, E. F. Y., & Elkhwesky, F. F. Y. (2023). Artificial intelligence in healthcare services: past, present and future research directions. Review of Managerial Science, 1-23.
  • Sihlahla, I., Donnelly, D. L., Townsend, B., & Thaldar, D. (2023). Legal and ethical principles governing the use of artificial intelligence in radiology services in South Africa. Developing World Bioethics.
  • Small, H. (2003). Paradigms, citations, and maps of science: A personal history. Journal of the American Society for information Science and Technology, 54(5), 394-399.
  • Sun, J., Wang, M.-H., & Ho, Y.-S. (2012). A historical review and bibliometric analysis of research on estuary pollution. Marine Pollution Bulletin, 64(1), 13-21.
  • Van Der Niet, A. G., & Bleakley, A. (2021). Where medical education meets artificial intelligence:‘Does technology care?’. Medical Education, 55(1), 30-36.
  • Zhang, J., & Zhang, Z.-M. (2023). Ethics and governance of trustworthy medical artificial intelligence. BMC Medical Informatics and Decision Making, 23(1), 7.
  • Zhang, Y., Wu, M., Tian, G. Y., Zhang, G., & Lu, J. (2021). Ethics and privacy of artificial intelligence: Understandings from bibliometrics. Knowledge-Based Systems, 222, 106994.
There are 35 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence (Other), Health Informatics and Information Systems, Health Management
Journal Section Research Articles
Authors

Ömer Çelik

Elif Kaya 0000-0002-1401-9947

Early Pub Date September 12, 2024
Publication Date August 31, 2024
Submission Date March 19, 2024
Acceptance Date August 10, 2024
Published in Issue Year 2024 Volume: 15 Issue: 43

Cite

APA Çelik, Ö., & Kaya, E. (2024). Artificial Intelligence and Ethics in Healthcare: A Bibliometric Analysis. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 15(43), 1046-1062. https://doi.org/10.21076/vizyoner.1455659

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