Sağlık Hizmetlerinde Yapay Zeka Kullanımının Risk Analizi ve Değerlendirmesi

Öz

Bu çalışma, büyük ölçekli reform, yenilikçi teknolojiler ve yapay zeka ile ilgili kanıta dayalı karar verme, paydaş koordinasyonu ve potansiyel hastalıkların ve pandemilerin izlenmesine odaklanarak Türkiye'deki sağlık sektöründeki temel sorunları tartışmayı amaçlamaktadır. Amaç, Türkiye'de sağlık sektöründe AI kullanımına yönelik uygulanabilir öneriler sunmaktır. Araştırmacılar literatür taramaları yaptılar ve çevrimiçi olarak AI ürünlerini/hizmetlerini aradılar. AI, sağlık da dahil olmak üzere çeşitli sektörlerde yenilikçi çözümler sunar. Gen bazlı, immün bazlı ve kök hücre rejenerasyon terapileri ve sentetik nano-biyoloji gibi ileri sağlık teknolojileri, daha öngörücü, önleyici, düzeltici, kişiselleştirilmiş ve katılımcı sağlık çözüm sistemlerine yol açabilir. Sağlıkla ilgili ürün ve yöntemlerin Ar-Ge süreci belirsizlikler, riskler ve fırsatlar içermektedir. Etik kaygılar, sosyal ilişkiler ve psikolojik ve yasal uyum seviyeleri, gelecekteki AI uygulamaları için önemli hususlardır. Yapay zekanın sağladığı toplumsal faydaları kabul ederken uzun vadeli yapay zeka araştırmaları ve politikaları oluşturmak çok önemlidir. Çalışma, teknolojik yenilikleri sağlık sektörüne entegre etmek için Türk makamlarına öneriler sunmaktadır.

Anahtar Kelimeler

• Anahtar Kelimeler: Sağlık YBS
• sosyal iyilik
• yapay zeka
• endüstri 4.0
• toplum 5.0

Risk Analysis and Assessment of Artificial Intelligence Usage in Healthcare

Öz

This study aims to discuss key issues in the health sector in Turkey, focusing on large-scale reform, evidence-based decision-making regarding innovative technologies and AI, stakeholder coordination, and monitoring of potential diseases and pandemics. The goal is to provide applicable suggestions for AI usage in the health sector in Turkey. The researchers conducted literature reviews and searched for AI products/services online. AI offers innovative solutions across various sectors, including health. Advanced health technologies, such as gene-based, immune-based, and stem cell regeneration therapies, and synthetic nano-biology, can lead to more predictive, preventive, corrective, personalized, and participatory health solution systems. The R&D process of health-related products and methods contains uncertainties, risks, and opportunities. Ethical concerns, social relations, and psychological and legal compliance levels are significant considerations for future AI applications. It is essential to create long-term AI research and policies while acknowledging the societal benefits AI provides. The study offers suggestions for Turkish authorities to integrate technological innovations into the health sector.

Anahtar Kelimeler

• Keywords: Health MIS
• social goodness
• artificial intelligence
• industry 4.0
• society 5.0

Kaynakça

1. AFP. (2018). Computer learns to detect skin cancer more accurately than doctors. The Guardian, https://www.theguardian.com/society/2018/may/29/skin-cancer-computer-learns-to-detect-skin-cancer-more-accurately-than-a-doctor
2. Berberich, N., Nishida, T. & Suzuki, S. (2020). Harmonizing artificial intelligence for social good. Philosophy and Technology, 33, 613-638. https://doi.org/10.1007/ s13347-020-00421-8
3. Brandon, B., Hsieh, J., Singh, A., Sohoni, N. & Wang, J. (2018.) DeepHeart: Semi-supervised sequence learning for cardiovascular risk prediction. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16967/15916
4. Butt, C., Gill, J., Chun, D. & Babu, B. A. (2020). Deep learning system to screen coronavirus disease 2019 pneumonia. Engineering, 6(10), 1122-1129. https://doi.org/10.1007/s10489-020-01714-3
5. Can, B., Başer, A., Baktır, Altuntaş, S., Özceylan, G. & Kolcu, G. (2021). Artificial Intelligence In Health Education. Süleyman Demirel Üniversitesi Tıp Fakültesi Dergisi, 28(2), 355-359.
6. CBC. (2016). Autism therapy wait list changes 'a difficult process,' minister acknowledges. CBC News, April 2, 2016. https://www.cbc.ca/news/canada/ottawa/autism-wait-list-ontario-minister-1.3517508
7. Chen, R. (2017). Briefing materials: Artificial intelligence and NASA data used to discover eighth planet circling distant star. National Aeronautics and Space Administration, December 20, 2017. https://www.nasa.gov/ames/kepler/briefing-materials-eighth-planet-circling-distant-star-discovered-using-artificial-intelligence
8. Chodosh, S. (2017). https://www.popsci.com/ pluto-might-be-planet-again/#page-2

9. Chou, F.H. (2018). Artificial intelligence, NASA data used to discover eighth planet circling distant star. NASA. https://www.nasa.gov/press-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star
10. Chui, M., Harryson, M., Manyika, J., Roberts, R., Chung, R., Heteren, A. & Nel, P. (2018). Notes from the AI frontier applying AI for social good, MCKINSEY Discussion Paper. https://t.ly/dpVl
11. EIU. (2019). World industry outlook: Healthcare and pharmaceuticals. Economist intelligence unit. Accessed: 22.12.2020. https://www2.deloitte.com/content/dam/Deloitte/cz/Documents/ life-sciences-health-care/2020-global-health-care-outlook.pdf
12. Fitzpatrick, K.K., Darcy, A. & Vierhile, M. (2017). Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Mental Health, 4(2), e19.
13. Forcier, M.B., Khoury, L. & Vézina, N. (2020). Liability issues for the use of artificial intelligence in health care in Canada: AI and medical decision-making. Dalhousie Medical Journal, 46(2).
14. Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A. & Webster, D.R. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. Journal of the American Medical Association, 316(22), 2402-2410.
15. GVR. (2019). Healthcare artificial intelligence (AI) market size, share and trends analysis report by application (robot-assisted surgery, virtual nursing assistant, dosage error reduction). Region, and segment forecasts, 2018 - 2025. https://www. grandviewresearch.com/industry-analysis/healthcare-artificial-intelligence-market
16. He, J., Baxter, S.L., Xu, J., Xu, J., Zhou, X. & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25(1), 30-36.
17. Henry, K.E., Hager, D.N., Pronovost, P.J. & Saria, S. (2015). A targeted real-time early warning score (TREWScore) for septic shock. Science Translational Medicine, 7(299), 299ra122.
18. Johnson, M. (2018), Kepler. NASA, https://www.nasa.gov/mission_pages/kepler/overview/index. html
19. Kandpal, V. & Khalaf, O.I. (2020). Artificial intelligence and SHGs: Enabling financial ınclusion in India. In: Sagayam, K., Bhushan, B., Andrushia, A. & Albuquerque V. (Ed.), Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks. Information Science Reference, pp.291-303. http://doi:10.4018/978-1-7998-5068-7.ch015
20. Kiper, M. (2013). Biotechnology Sectoral Innovation System. Concepts, Examples from the world, situation and inferences in Turkey. https://ttgv.org.tr/tr/yayinlar/ bioteknoloji-sektorel-inovasyon-sistemi Kurtkapan, H. (2019). Social Reflections of Demographic Transformation and Aging in Turkey. https://dergipark.org.tr/ en/download/article-file/771944
21. Kuziemsky, C., Maeder, A.J., John, O., Gogia, S.B., Basu, A. Meher, S. & Ito, M. (2019). Role of artificial intelligence within the telehealth domain. IMIA and Georg Thieme Verlag KG Official Yearbook Contribution by the members of IMIA. Telehealth Working Group, https://www.thieme-connect.com/products/ejournals/pdf/10.1055/s-0039-1677897.pdf
22. Mamdani, E.H., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1), 1-13.
23. Markets and Markets. (2019). Artificial intelligence in healthcare market by offering (hardware, software, services), technology (machine learning, natural language processing), application (robot-assisted surgery, virtual nursing assistant), end user, and geography - global forecast to 2025. https://www.marketsandmarkets.com/Market-Reports/ai-in-healthcare-market-568.html
24. Pham, Q., Gamble, A., Hearn, J. & Cafazzo, J.A. (2021). The need for ethnoracial equity in artificial intelligence for diabetes management: Review and recommendations. Journal of Medical Internet Research, 23(2), e22320. 10.2196/22320
25. Porayska-Pomsta, K. & Rajendran, G. (2019) Accountability in human and artificial intelligence decision-making as the basis for diversity and educational inclusion. In: Knox, J., Wang, Y., Gallagher, M. (eds), Artificial Intelligence and Inclusive Education. Perspectives on Rethinking and Reforming Education. Springer, Singapore. https://doi.org/ 10.1007/978-981-13-8161-4_3
26. Price, W.N., Cohen, I.G. & Daniel, F. (2019). Privacy in the age of medical big data. Nature Medicine, 25(1), 37-43.
27. Probst, L. et al. (2014). Smart Living: Connected devices for intelligent homes, Case study 20. European Union. https://ec.europa.eu/docsroom/documents/13407/attachments/5/translations/en/renditions/ native
28. Rajasekera, J. (2020) How AI Can Bring About Social Good, Development Asia. https://development.asia/explainer/how-ai-can-bring-about-social-good
29. Ryan, S.Z., Claire, W. & Fei, F. (2020). Artificial Intelligence for Social Good: A Survey. Computers and Society, https://arxiv.org/abs/2001.01818
30. Shallue, J.S. & Vanderburg, A. (2011). Identıfyıng Exoplanets Wıth Deep Learnıng: A Fıve Planet Resonant Chaın Around Kepler-80 And An Eıghth Planet Around Kepler-90, https://lweb.cfa.harvard.edu/~avanderb/kepler90i.pdf
31. TCCB-DDO. (2020). Büyük Beyin Projesi. https://cbddo.gov.tr/haberler/4890/turkiye-de-bir-ilk-turk-beyin-projesi-cumhurbaskanligi-dijital-donusum-ofisi-ve-gazi-universitesi-is-birligi-ile-hayata-gecirildi-
32. Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Hachette UK.
33. Tran, D.M., Rauschecker, A.M., Rudie, J.D., Chen, P.H., Cook, T.S., Bryan, R.N. & Mohan, S. (2019). Artificial intelligence for precision education in radiology. The British Journal of Radiology, 92(1103), 20190389. https://doi.org/10.1259/bjr.20190389
34. Tzachor, A., Whittlestone, J., Sundaram, L. & hÉigeartaigh, S.Ó. (2020). Artificial intelligence in a crisis needs ethics with urgency. Nature Machine Intelligence, 2, 365-366 https://doi.org/10.1038/s42256-020-0195-0
35. van der Schaar, M., Alaa, A.M., Floto, A, Gimson, A., Scholtes, S., Wood, A., McKinney, ., Jarrett, D., Lio, P. & Ercole, A. (2021). How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Machine Learning, 110, 1-14. http://www.vanderschaar-lab.com/NewWebsite/covid-19/post1/paper.pdf
36. Wang, Kang, B., Ma, J., Zeng, X., Xiao, M, Guo, J., Cai, M., Yang, J., Li, y., Meng, X. & Xu, B. (2020). A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19). MedRxiv. https://doi.org/10.1101/2020.02.14.20023028
37. WEF. (2019). Health and healthcare in the fourth industrial revolution global future council on the future of health and healthcare 2016-2018. World Economic Forum: https://www. weforum.org/reports/health-and-healthcare-in-the-fourth-industrial-revolution-global-future-council-on-the-future-of-health-and-healthc are-2016-2018
38. WHO. (2016). World Health Organization. (t.y.) Projections of mortality and causes of death, to 2060. Health statistics and information systems.
39. Yılmaz, A. & Ölçer, İ. (2021). Yapay zekanin cerrahi uygulamalara entegrasyonu. Beykent Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 13 (2), 21-27. DOI: 10.20854/bujse.873770
40. Yılmaz, Y., Uzelli, Y.D., Yıldırım, D., Akın, K.E., Öze, K.D., Zekâ, Y. (2021). Sağlıkta yapay zekanın kullanımına yönelik sağlık bilimleri fakültesi öğrencilerinin görüşleri. Süleyman Demirel Üniversitesi Sağlık Bilimleri Dergisi, 12(3), 297-308.
41. Zadeh, L. A. (2008). Fuzzy logic and ambient intelligence. Journal of Advanced Computational Intelligence and Intelligent Informatics, 12(4), 317-324.
42. Zhan, Z., Genc, Y., Xing, A., Wang, D., Fan, X. & Citardi, D. (2020). Lay individuals' perceptions of artificial intelligence (AI)-empowered healthcare systems. Proceedings of the Association for Information Science and Technology,5(1), e326. https://doi.org/10.1002/pra2.326
43. Zhang, H., Saravanan, K.M., Yang, Y., Hossain, T., Li, J., Ren, X., Pan, Y. Wei, Y. (2020). Deep learning based drug screening for novel coronavirus 2019-nCov. Interdiscip Science, 12(3), 368-376. https://doi.org/10.20944/preprints202002.0061.v1