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Use of Artificial Intelligence and Big Data Management in Healthcare Institutions

Year 2024, Volume: 2 Issue: 2, 193 - 196, 30.12.2024

Abstract

Medical AI is one of the hot topics in the research and applied fields of medicine. Various research mention privacy as a major ethical challenge for medical uses of AI. The good news is most of the AI tools are design to replace physician but to assist them. This reduces ethical challenges, while not eliminating all. Researchers state that although we are far from consensus in ethical uses of medical AI, we have more or less an agreement on key principles. If the medical data to be used to train AI is from a narrow sample of patients, it can err with larger groups. On the other hand, some other problems can be due to users. Thus, development of AI literacy is necessary. In other words, they have to learn which AI tools to use for various purposes. When we consider early versions of medical AI, we realize that they mad sense for explanation and teaching, but fail as an assistant for clinical practice, but this situation has been changing rapidly. Medical students are highly positive of medical AI, and believe that it will not replace but complement human doctors. There is a realistic anxiety that in a group of medical areas, especially radiology, AI will outperform human doctors. AI anxiety can also be due to perceived difficulty to use AI. A solution to ethical problems in medical AI is trustworthy AI model.

References

  • [1] Shreve, J. T., Khanani, S. A., & Haddad, T. C. Artificial intelligence in oncology: current capabilities, future opportunities, and ethical considerations. American Society of Clinical Oncology Educational Book, 42, 842-851, 2022.
  • [2] Jin, S., Wang, B., Xu, H., Luo, C., Wei, L., Zhao, W., ... & Xu, W. AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system in four weeks. MedRxiv, 2020-03, 2020.
  • [3] Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. AI in health and medicine. Nature medicine, 28(1), 31-38, 2022.
  • [4] Wang, B., Jin, S., Yan, Q., Xu, H., Luo, C., Wei, L., ... & Dong, J. AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system. Applied soft computing, 98, 106897, 2021.
  • [5] Yang, Y., Zhang, H., Gichoya, J. W., Katabi, D., & Ghassemi, M. The limits of fair medical imaging AI in real- world generalization. Nature Medicine, 1-11, 2024.
  • [6] Alvarado, R. Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI. Bioethics, 36(2), 121-133, 2022.
  • [7] Price, W., & Nicholson, I. I. Medical AI and contextual bias. Harv. JL & Tech., 2019; 33, 65.
  • [8] Di Nucci, E. Should we be afraid of medical AI?. Journal of Medical Ethics, 45(8), 556-558, 2019.
  • [9] Durán, J. M., & Jongsma, K. R. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI. Journal of Medical Ethics, 47(5), 329- 335, 2021.
  • [10] Ferrario, A., Loi, M., & Viganò, E. Trust does not need to be human: it is possible to trust medical AI. Journal of Medical Ethics, 47(6), 437-438, 2021.
  • [11] Kerasidou, C. X., Kerasidou, A., Buscher, M., & Wilkinson, S. Before and beyond trust: reliance in medical AI. Journal of medical ethics, 48(11), 852-856, 2022.
  • [12] Kundu, S. Measuring trustworthiness is crucial for medical AI tools. Nature Human Behaviour, 7(11), 1812- 1813, 2023.
  • [13] Mainz, J. T. Medical AI: is trust really the issue?. Journal of Medical Ethics, 50(5), 349-350, 2024.
  • [14] Malešević, A., Kolesárová, M., & Čartolovni, A. Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study. BMC Medical Ethics, 25(1), 94, 2024.
  • [15] Quinn, T. P., Senadeera, M., Jacobs, S., Coghlan, S., & Le, V. Trust and medical AI: the challenges we face and the expertise needed to overcome them. Journal of the American Medical Informatics Association, 28(4), 890- 894, 2021.
  • [16] Zuchowski, L. C., Zuchowski, M. L., & Nagel, E. A trust based framework for the envelopment of medical AI. Digital Medicine, 7(1), 230, 2024.
  • [17] Huo, W., Yuan, X., Li, X., Luo, W., Xie, J., & Shi, B. Increasing acceptance of medical AI: the role of medical staff participation in AI development. International journal of medical informatics, 175, 105073, 2023.
  • [18] Estiri, H., Strasser, Z. H., Rashidian, S., Klann, J. G., Wagholikar, K. B., McCoy Jr, T. H., & Murphy, S. N. An objective framework for evaluating unrecognized bias in medical AI models predicting COVID-19 outcomes. Journal of the American Medical Informatics Association, 29(8), 1334-1341, 2022.
  • [19] Ganz, M., Holm, S. H., & Feragen, A. Assessing bias in medical ai. In Workshop on Interpretable ML in Healthcare at International Connference on Machine Learning (ICML), 2021.
  • [20] Truhn, D., Müller-Franzes, G., & Kather, J. N. The ecological footprint of medical AI. European Radiology, 34(2), 1176-1178, 2024.
  • [21] Marcu, L. G., Boyd, C., & Bezak, E. Current issues regarding artificial intelligence in cancer and health care. Implications for medical physicists and biomedical engineers. Health and Technology, 9, 375-381, 2019.
  • [22] Ostherr, K. Artificial intelligence and medical humanities. Journal of Medical Humanities, 43(2), 211- 232, 2022.
  • [23] Price, W. N., & Cohen, I. G. Privacy in the age of medical big data. Nature medicine, 25(1), 37-43, 2019.
  • [24] Singh, J. P. The Impacts and Challenges of Generative Artificial Intelligence in Medical Education, Clinical Diagnostics, Administrative Efficiency, and Data Generation. International Journal of Applied Health Care Analytics, 8(5), 37-46, 2023.
  • [25] Vandemeulebroucke, T. The ethics of artificial intelligence systems in healthcare and medicine: from a local to a global perspective, and back. Pflügers Archiv- European Journal of Physiology, 1-11, 2024.
  • [26] Hu, Z., Hu, R., Yau, O., Teng, M., Wang, P., Hu, G., & Singla, R. Tempering expectations on the medical artificial intelligence revolution: the medical trainee viewpoint. JMIR Medical Informatics, 10(8), e34304, 2022.
  • [27] Feng, Q. J., Harte, M., Carey, B., Alqarni, A., Monteiro, L., Diniz‐Freitas, M., ... & Albuquerque, R. The risks of artificial intelligence: A narrative review and ethical reflection from an Oral Medicine group. Oral diseases, 2024.
  • [28] Möllmann, N. R., Mirbabaie, M., & Stieglitz, S. Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations. Health informatics journal, 27(4), 14604582211052391, 2021.
  • [29] Maccaro, A., Stokes, K., Statham, L., He, L., Williams, A., Pecchia, L., & Piaggio, D. Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices. Journal of Personalized Medicine, 14(5), 443, 2024.
  • [30] Bommu, R. Ethical Considerations in the Development and Deployment of AI-powered Medical Device Software: Balancing Innovation with Patient Welfare. Journal of Innovative Technologies, 5(1), 1-7, 2022.
  • [31] Masters, K. Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574-584, 2023.
  • [32] Müller, H., Mayrhofer, M. T., Van Veen, E. B., & Holzinger, A. The Ten Commandments of Ethical Medical AI. Computer, 54(7), 119-123, 2021.
  • [33] Franco D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. M. Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education. Medical Education Online, 29(1), 2330250, 2024.
  • [34] Uygun İlikhan, S., Özer, M., Tanberkan, H., & Bozkurt, VHow to mitigate the risks of deployment of artificial intelligence in medicine?. Turkish Journal of Medical Sciences, 54(3), 483-492, 2024..
  • [35] Gezgin, U.B. AI Literacy: A Practical Exploration Through the Uses of AI Tools. 17. Ejons Uluslararası Kongresi "Teorikten Pratiğe Yapay Zeka ve Toplum", 21-22 Ağustos 2024. (pp.276-280). Institute Of Economic Development And Social Researches Publications. ISBN: 978-625-367-813-5; 2024. https://www.ejonscongress.org/_files/ugd/614b1f_9620 e8520c414a58bf8e9bf2f2da285e.pdf
  • [36] Kulikowski, C. A. Beginnings of artificial intelligence in medicine (AIM): computational artifice assisting scientific inquiry and clinical art–with reflections on present aim challenges. Yearbook of medical informatics, 28(01), 249-256, 2019.
  • [37] Bélisle-Pipon, J. C., Couture, V., Roy, M. C., Ganache, I., Goetghebeur, M., & Cohen, I. G. What makes artificial intelligence exceptional in health technology assessment?. Frontiers in artificial intelligence, 4, 736697, 2021.
  • [38] Rosemann, A., & Zhang, X. Exploring the social, ethical, legal, and responsibility dimensions of artificial intelligence for health-a new column in Intelligent Medicine. Intelligent Medicine, 2(02), 103-109, 2022.
  • [39] Alolabi, H., & Aarthy, C. C. J. Ethical Challenges Presented by Advanced Artificial Intelligence in Diagnostics and Treatment Recommendations. Journal of Empirical Social Science Studies, 5(1), 30-47, 2021.
  • [40] Cadario, R., Longoni, C., & Morewedge, C. K. Understanding, explaining, and utilizing medical artificial intelligence. Nature human behaviour, 5(12), 1636-1642, 2021.
  • [41] Zhang, J., & Zhang, Z. M. Ethics and governance of trustworthy medical artificial intelligence. BMC medical informatics and decision making, 23(1), 7, 2023.

Use of Artificial Intelligence and Big Data Management in Healthcare Institutions

Year 2024, Volume: 2 Issue: 2, 193 - 196, 30.12.2024

Abstract

Tıbbi YZ, tıbbın araştırma ve uygulama alanlarındaki sıcak konulardan biridir. Çeşitli araştırmalar, YZ'nin tıbbi kullanımları için önemli bir etik zorluk olarak gizlilikten bahsetmektedir. İyi haber şu ki, YZ araçlarının çoğu hekimin yerini almak için değil, onlara yardımcı olmak için tasarlanmıştır. Bu, etik zorlukları azaltırken, hepsini ortadan kaldırmamaktadır. Araştırmacılar, tıbbi YZ'nin etik kullanımları konusunda fikir birliğinden uzak olsak da, temel ilkeler üzerinde aşağı yukarı bir anlaşmaya sahip olduğumuzu belirtiyor. YZ'yi eğitmek için kullanılacak tıbbi veriler dar bir hasta örneğinden geliyorsa, daha büyük gruplarda hata yapabilir. Öte yandan, diğer bazı sorunlar kullanıcılardan kaynaklanabilir. Bu nedenle, YZ okuryazarlığının geliştirilmesi gereklidir. Başka bir deyişle, çeşitli amaçlar için hangi YZ araçlarını kullanacaklarını öğrenmeleri gerekir. Tıbbi YZ'nin ilk versiyonlarını düşündüğümüzde, açıklama ve öğretim için mantıklı olduklarını, ancak klinik uygulama için bir asistan olarak başarısız olduklarını fark ediyoruz, ancak bu durum hızla değişiyor. Tıp öğrencileri tıbbi YZ'ye son derece olumlu yaklaşıyor ve insan doktorların yerini almayacağına ancak onları tamamlayacağına inanıyor. Radyoloji başta olmak üzere bir grup tıbbi alanda YZ'nin insan doktorlardan daha iyi performans göstereceğine dair gerçekçi bir endişe vardır. YZ kaygısı, YZ'yi kullanmanın algılanan zorluğundan da kaynaklanabilir. Tıbbi YZ'deki etik sorunlara bir çözüm, güvenilir YZ modelidir.

References

  • [1] Shreve, J. T., Khanani, S. A., & Haddad, T. C. Artificial intelligence in oncology: current capabilities, future opportunities, and ethical considerations. American Society of Clinical Oncology Educational Book, 42, 842-851, 2022.
  • [2] Jin, S., Wang, B., Xu, H., Luo, C., Wei, L., Zhao, W., ... & Xu, W. AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system in four weeks. MedRxiv, 2020-03, 2020.
  • [3] Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. AI in health and medicine. Nature medicine, 28(1), 31-38, 2022.
  • [4] Wang, B., Jin, S., Yan, Q., Xu, H., Luo, C., Wei, L., ... & Dong, J. AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system. Applied soft computing, 98, 106897, 2021.
  • [5] Yang, Y., Zhang, H., Gichoya, J. W., Katabi, D., & Ghassemi, M. The limits of fair medical imaging AI in real- world generalization. Nature Medicine, 1-11, 2024.
  • [6] Alvarado, R. Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI. Bioethics, 36(2), 121-133, 2022.
  • [7] Price, W., & Nicholson, I. I. Medical AI and contextual bias. Harv. JL & Tech., 2019; 33, 65.
  • [8] Di Nucci, E. Should we be afraid of medical AI?. Journal of Medical Ethics, 45(8), 556-558, 2019.
  • [9] Durán, J. M., & Jongsma, K. R. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI. Journal of Medical Ethics, 47(5), 329- 335, 2021.
  • [10] Ferrario, A., Loi, M., & Viganò, E. Trust does not need to be human: it is possible to trust medical AI. Journal of Medical Ethics, 47(6), 437-438, 2021.
  • [11] Kerasidou, C. X., Kerasidou, A., Buscher, M., & Wilkinson, S. Before and beyond trust: reliance in medical AI. Journal of medical ethics, 48(11), 852-856, 2022.
  • [12] Kundu, S. Measuring trustworthiness is crucial for medical AI tools. Nature Human Behaviour, 7(11), 1812- 1813, 2023.
  • [13] Mainz, J. T. Medical AI: is trust really the issue?. Journal of Medical Ethics, 50(5), 349-350, 2024.
  • [14] Malešević, A., Kolesárová, M., & Čartolovni, A. Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study. BMC Medical Ethics, 25(1), 94, 2024.
  • [15] Quinn, T. P., Senadeera, M., Jacobs, S., Coghlan, S., & Le, V. Trust and medical AI: the challenges we face and the expertise needed to overcome them. Journal of the American Medical Informatics Association, 28(4), 890- 894, 2021.
  • [16] Zuchowski, L. C., Zuchowski, M. L., & Nagel, E. A trust based framework for the envelopment of medical AI. Digital Medicine, 7(1), 230, 2024.
  • [17] Huo, W., Yuan, X., Li, X., Luo, W., Xie, J., & Shi, B. Increasing acceptance of medical AI: the role of medical staff participation in AI development. International journal of medical informatics, 175, 105073, 2023.
  • [18] Estiri, H., Strasser, Z. H., Rashidian, S., Klann, J. G., Wagholikar, K. B., McCoy Jr, T. H., & Murphy, S. N. An objective framework for evaluating unrecognized bias in medical AI models predicting COVID-19 outcomes. Journal of the American Medical Informatics Association, 29(8), 1334-1341, 2022.
  • [19] Ganz, M., Holm, S. H., & Feragen, A. Assessing bias in medical ai. In Workshop on Interpretable ML in Healthcare at International Connference on Machine Learning (ICML), 2021.
  • [20] Truhn, D., Müller-Franzes, G., & Kather, J. N. The ecological footprint of medical AI. European Radiology, 34(2), 1176-1178, 2024.
  • [21] Marcu, L. G., Boyd, C., & Bezak, E. Current issues regarding artificial intelligence in cancer and health care. Implications for medical physicists and biomedical engineers. Health and Technology, 9, 375-381, 2019.
  • [22] Ostherr, K. Artificial intelligence and medical humanities. Journal of Medical Humanities, 43(2), 211- 232, 2022.
  • [23] Price, W. N., & Cohen, I. G. Privacy in the age of medical big data. Nature medicine, 25(1), 37-43, 2019.
  • [24] Singh, J. P. The Impacts and Challenges of Generative Artificial Intelligence in Medical Education, Clinical Diagnostics, Administrative Efficiency, and Data Generation. International Journal of Applied Health Care Analytics, 8(5), 37-46, 2023.
  • [25] Vandemeulebroucke, T. The ethics of artificial intelligence systems in healthcare and medicine: from a local to a global perspective, and back. Pflügers Archiv- European Journal of Physiology, 1-11, 2024.
  • [26] Hu, Z., Hu, R., Yau, O., Teng, M., Wang, P., Hu, G., & Singla, R. Tempering expectations on the medical artificial intelligence revolution: the medical trainee viewpoint. JMIR Medical Informatics, 10(8), e34304, 2022.
  • [27] Feng, Q. J., Harte, M., Carey, B., Alqarni, A., Monteiro, L., Diniz‐Freitas, M., ... & Albuquerque, R. The risks of artificial intelligence: A narrative review and ethical reflection from an Oral Medicine group. Oral diseases, 2024.
  • [28] Möllmann, N. R., Mirbabaie, M., & Stieglitz, S. Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations. Health informatics journal, 27(4), 14604582211052391, 2021.
  • [29] Maccaro, A., Stokes, K., Statham, L., He, L., Williams, A., Pecchia, L., & Piaggio, D. Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices. Journal of Personalized Medicine, 14(5), 443, 2024.
  • [30] Bommu, R. Ethical Considerations in the Development and Deployment of AI-powered Medical Device Software: Balancing Innovation with Patient Welfare. Journal of Innovative Technologies, 5(1), 1-7, 2022.
  • [31] Masters, K. Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574-584, 2023.
  • [32] Müller, H., Mayrhofer, M. T., Van Veen, E. B., & Holzinger, A. The Ten Commandments of Ethical Medical AI. Computer, 54(7), 119-123, 2021.
  • [33] Franco D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. M. Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education. Medical Education Online, 29(1), 2330250, 2024.
  • [34] Uygun İlikhan, S., Özer, M., Tanberkan, H., & Bozkurt, VHow to mitigate the risks of deployment of artificial intelligence in medicine?. Turkish Journal of Medical Sciences, 54(3), 483-492, 2024..
  • [35] Gezgin, U.B. AI Literacy: A Practical Exploration Through the Uses of AI Tools. 17. Ejons Uluslararası Kongresi "Teorikten Pratiğe Yapay Zeka ve Toplum", 21-22 Ağustos 2024. (pp.276-280). Institute Of Economic Development And Social Researches Publications. ISBN: 978-625-367-813-5; 2024. https://www.ejonscongress.org/_files/ugd/614b1f_9620 e8520c414a58bf8e9bf2f2da285e.pdf
  • [36] Kulikowski, C. A. Beginnings of artificial intelligence in medicine (AIM): computational artifice assisting scientific inquiry and clinical art–with reflections on present aim challenges. Yearbook of medical informatics, 28(01), 249-256, 2019.
  • [37] Bélisle-Pipon, J. C., Couture, V., Roy, M. C., Ganache, I., Goetghebeur, M., & Cohen, I. G. What makes artificial intelligence exceptional in health technology assessment?. Frontiers in artificial intelligence, 4, 736697, 2021.
  • [38] Rosemann, A., & Zhang, X. Exploring the social, ethical, legal, and responsibility dimensions of artificial intelligence for health-a new column in Intelligent Medicine. Intelligent Medicine, 2(02), 103-109, 2022.
  • [39] Alolabi, H., & Aarthy, C. C. J. Ethical Challenges Presented by Advanced Artificial Intelligence in Diagnostics and Treatment Recommendations. Journal of Empirical Social Science Studies, 5(1), 30-47, 2021.
  • [40] Cadario, R., Longoni, C., & Morewedge, C. K. Understanding, explaining, and utilizing medical artificial intelligence. Nature human behaviour, 5(12), 1636-1642, 2021.
  • [41] Zhang, J., & Zhang, Z. M. Ethics and governance of trustworthy medical artificial intelligence. BMC medical informatics and decision making, 23(1), 7, 2023.
There are 41 citations in total.

Details

Primary Language English
Subjects Data Engineering and Data Science
Journal Section Research Articles
Authors

İpek Eroğlu 0000-0002-6980-4192

Ulaş Başar Gezgin

Publication Date December 30, 2024
Submission Date November 26, 2024
Acceptance Date December 13, 2024
Published in Issue Year 2024 Volume: 2 Issue: 2

Cite

IEEE İ. Eroğlu and U. B. Gezgin, “Use of Artificial Intelligence and Big Data Management in Healthcare Institutions”, CÜMFAD, vol. 2, no. 2, pp. 193–196, 2024.