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DOI :10.26650/acin.750857   IUP :10.26650/acin.750857    Full Text (PDF)

Artificial Intelligence in Health Services and Management

Betül Akalın, Ülkü Veranyurt

Increasing chronic diseases and epidemics, such as the Covid-19 pandemic, shows a greater need in home care services of the elderly population due to the prolongation of the average human life span and changes in the expectations of individuals from health services in parallel with the development of health literacy. It also brings about change in health services and management. The cooperation of health services and management, the health sector and othersectors would benefit a wide audience. Health professionals and other occupational groups should be able to work in coordination. In addition, there is a need to use health information technologies in the diagnosis, treatment, rehabilitation of diseases and in the management of health services for the development of public health. Considering all of these, it is inevitable to use artificial intelligence applications in healthcare services and management due to the increasing workload and insufficient number of health workers. A patient-oriented digital health ecosystem is being created in line with current developments in healthcare and technology. It is recommended to make the necessary legal regulations in the use of artificial intelligence applications with promising solutions. 

Keywords: Healthcare, Healthcare Management, Artificial Intelligence
DOI :10.26650/acin.750857   IUP :10.26650/acin.750857    Full Text (PDF)

Sağlık Hizmetleri ve Yönetiminde Yapay Zekâ

Betül Akalın, Ülkü Veranyurt

Günümüzde artan kronik hastalıklar, Covid-19 pandemisi gibi salgınlar, ortalama insan ömrünün uzamasına bağlı olarak artan yaşlı nüfusun evde bakım hizmetlerine olan ihtiyacının artışı ve sağlık okuryazarlığının gelişmesine paralel olarak bireylerin sağlık hizmetlerinden beklentilerindeki değişiklikler; sağlık hizmetleri ve yönetiminde de değişimi beraberinde getirmektedir. Sağlık hizmetleri ve yönetimi, sağlık sektörü ve diğer sektörlerin işbirliği ile geniş kitlelere hitap etmektedir. Sağlık profesyonelleri ile birlikte diğer meslek gruplarının bir arada koordineli bir şekilde çalışabilmesi gerekmektedir. Bunun yanında hastalıkların tanı, tedavi, rehabilitasyonunda ve toplum sağlığının geliştirilmesinde sağlık hizmetlerinin yönetiminde sağlık bilgi teknolojilerinin kullanımına ihtiyaç vardır. Tüm bunlar dikkate alındığında, artan iş yükü yanında yetersiz sayıdaki sağlık insan gücü sebebi ile sağlık hizmetleri ve yönetiminde yapay zekâ uygulamalarının kullanılması kaçınılmazdır. Sağlık alanında ve teknolojide güncel gelişmeler doğrultusunda hasta odaklı dijital bir sağlık ekosistemi yaratılmaya başlanmıştır. Umut vaat eden çözümleriyle yapay zekâ uygulamalarının kullanımında gerekli yasal düzenlemelerin yapılması önerilmektedir.

Keywords: Sağlık Hizmetleri, Sağlık Hizmetleri Yönetimi, Yapay Zekâ

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References

  • Veranyurt U, Deveci AF, Esen MF, Veranyurt O. (2020). Disease Classification By Machine Learning Techniques: Random Forest, K-Nearest Neighbor and Adaboost Algorithms Applications. Usaysad Derg. 2020; 6(2):275-286. google scholar
  • Hayran O. (2012). Sağlık Yönetimi Yazıları. Ankara: Sage Yayıncılık. google scholar
  • Elmas Ç. 2018. Yapay Zekâ Uygulamaları. 4. Baskı. Ankara: Seçkin Yayıncılık, 25-45. google scholar
  • Akalın B. 2020. Sağlık Hizmetleri ve Yönetiminde Yapay Zekâ. İstanbul: Hiper Yayıncılık, 125-132. google scholar
  • Qian, Z., Alaa, A. M., & van der Schaar, M. (2020). CPAS: the UK’s National Machine Learning-based Hospital Capacity Planning System for COVID-19. google scholar
  • Jiang F, Jiang Y, Zhi H, et al. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology;2: e000101. doi:10.1136/ svn-2017-000101. google scholar
  • OECD. Organisation for Economic Co-operation and Development. (2019). Health at a Glance 2019: OECD Indicators. Paris: OECD Publishing; 2019. doi:10.1787/4dd50c09-en. google scholar
  • TUİK. Türkiye İstatistik Kurumu. https://www.tuik.gov.tr/ (Erişim Tarihi: 01.11.2020). google scholar
  • Öcal H., Doğru İ. A. ve Barışçı N. (2019). Akıllı ve geleneksel giyilebilir sağlık cihazlarında nesnelerin interneti. Politeknik Dergisi, 22(3): 695-714. T.C. Sağlık Bakanlığı Sağlık İstatistikleri Yıllığı 2018. https://dosyasb.saglik.gov.tr/Eklenti/36134,siy2018trpdf.pdf?0 (Erişim Tarihi: 01.11.2020). google scholar
  • Çoban, H. (2009). Sağlık Ekonomisi ve Türkiye’de Sağlık Hizmetlerinin Yeniden Yapılandırılması. Dokuz Eylül Üniversitesi, Doktora Tezi, İzmir. google scholar
  • World Health Organization (WHO). “Ten threats to global health in 2019”, https://www.who.int/emergencies/ten-threats-to-global- health-in-2019 (Erişim Tarihi: 01.11.2020). google scholar
  • Fleming, N. (2018). How Artificial intelligence is changing drug discovery. Naature, 557(7707), ss 55-57. Doi: 10.1038/d41586-018-05267-x. google scholar
  • Hecht, D. (2011). Applications of Machine Learning and Computational Intelligence to Drug Discovery and Development. Drug Development Research, 72: 53-65. google scholar
  • Gavin, B., Hayden, J., Adamis, D., & McNicholas, F. (2020). Caring for the psychological well-being of healthcare professionals in the Covid-19 pandemic crisis. Ir Med J, 113(4), 51. google scholar
  • Mesko, B. (2017). Yapay Zekâyla Tıbbi Karar Almak. B. Mesko içinde, Tıbbın Geleceğine Yolculuk (s. 174-183). İstanbul: Optimist Yayın Grubu. google scholar
  • Kadri, F., Baraoui, M., & Nouaouri, I. (2019, September). An LSTM-based Deep Learning Approach with Application to Predicting Hospital Emergency Department Admissions. In 2019 International Conference on Industrial Engineering and Systems Management (IESM) IEEE. (1-6). google scholar
  • İntel. (2018). Sağlık Dönüşümü. https://www.intel.com.tr/content/www/tr/tr/healthcare-it/healthcare-overview.html (Erişim Tarihi: 01.11.2020). google scholar
  • Triantafyllidis, A., Polychronidou, E., Alexiadis, A., Rocha, C. L., Oliveira, D. N., da Silva, A. S., Freire, A. L., Macedo, C., Sousa, I. F., Werbet, E., Lillo, E. A., Luengo, H. G., Ellacuria, M. T., Votis, K., & Tzovaras, D. (2020). Computerized decision support and machine learning applications for the prevention and treatment of childhood obesity: A systematic review of the literature. Artificial Intelligence In Medicine, 104. google scholar
  • T.C. Sağlık Bakanlığı Sağlık Bilgi Sistemleri Genel Müdürlüğü, FİTAS (Filyasyon ve İzolasyon Takip Sistemi). https://sbsgm.saglik.gov.tr/TR,73584/ fitas.html (Erişim Tarihi: 01.11.2020). google scholar
  • Yan, Y. (2020). MCI progression classification for early diagnosis of Alzheimer’s disease using machine learning and deep learning methods. Res. Biomed. 36:311-331. google scholar
  • Curioni-Fontecedro, A. (2017). A new era of oncology through artificial intelligence. ESMO Open; 2(2): e000198. google scholar
  • Larson, D.B., Chen, M.C., Lungren, M.P., Halabi, S.S., Stence, N.V., Langlotz, C.P. 2018. Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs. Radiology 287, 313-322. google scholar
  • Somashekhar, S.P., Sepulveda, M.J., Puglielli, S., Norden, A.D., Shortliffe, E.H., Rohit Kumar, C., Rauthan, A., Arun Kumar, N., Patil, P., Rhee, K., Ramya, Y. 2018. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board. Ann. Oncol. 29, 418-423. google scholar
  • Long E, Lin H, Liu Z, et al. 2017. An artificial intelligence platform for the multihospital collaborative management of congenital cataracts. Nat Biomed Eng;1. Article number 24. google scholar
  • Ting, D. S. W., Pasquale, L. R., Peng, L., Campbell, J. P., Lee, A. Y., Raman, R., ... & Wong, T. Y. (2019). Artificial intelligence and deep learning in ophthalmology. British Journal of Ophthalmology, 103(2), 167-175. google scholar
  • Guo J, Li B (2018) The application of medical artificial intelligence technology in rural areas of developing countries, Health Equity 2:1, 174-181. google scholar
  • Zheng, L., Lin, F., Zhu, C., Liu, G., Wu, X., Wu, Z., Zheng, J., Xia, H., Cai, Y., & Liang, H. (2020). Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections. BioMed Research International, 1-11. google scholar
  • Pedrosa, T. L, Vasconcelos, F. F., Medeiros, L., & Silva, L. D. (2018). Machine Learning Application to Quantify the Tremor Level for Parkinson’s Disease Patients. Procedia Computer Science, 138, 215-220. google scholar
  • Muraro, C., Polato, M., Bortoli, M., Aiolli, F., & Orian, L. (2020). Radical scavenging activity of natural antioxidants and drugs: Development of a combined machine learning and quantum chemistry protocol. Journal of Chemical Physics, 153(11), 1. google scholar
  • Thadatritharntip, W., & Vongurai, R. (2020). Artificial Intelligence Healthcare: An Empirical Study on Users’ Attitude and Intention to Use toward a Personal Home Healthcare Robot to Improve Health and Wellness Conditions in Bangkok, Thailand. UTCC International Journal of Business & Economics, 12(1), 3-25. google scholar
  • Itkonen, P. (2019). Artificial intelligence in Home Care Settings in South Karelia Social and Healthcare District in Finland. 2019 IEEE World Congress on Services (SERVICES), 2642-939X, 238-239. google scholar
  • Şensu S, Erdoğan N, Gürbüz, YS. 2020. Patolojide Dijital Çağ ve Yapay Zekâ: Temel Bilgiler. Türkiye Klinikleri J Med Sci; 40(1):104-12. google scholar
  • Oral, C. 2011. Sayısal Mamografi Görüntülerine Yapay Zekâ Yöntemlerinin Uygulanması. Doktora Tezi, Ondokuz Mayıs Üniversitesi, Samsun, 35-56. google scholar
  • Thinktech STM. İleri Sağlık Teknolojileri I - Akıllı Sağlık Uygulamaları Ve Veri Analizi İle Sağlık Sorunlarını Tanımlamak (Araştırma Raporu 2019). http://thinktech.stm.com.tr (Erişim Tarihi: 01.11.2020). google scholar

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APA

Akalın, B., & Veranyurt, Ü. (2021). Artificial Intelligence in Health Services and Management. Acta Infologica, 5(1), 231-240. https://doi.org/10.26650/acin.750857


AMA

Akalın B, Veranyurt Ü. Artificial Intelligence in Health Services and Management. Acta Infologica. 2021;5(1):231-240. https://doi.org/10.26650/acin.750857


ABNT

Akalın, B.; Veranyurt, Ü. Artificial Intelligence in Health Services and Management. Acta Infologica, [Publisher Location], v. 5, n. 1, p. 231-240, 2021.


Chicago: Author-Date Style

Akalın, Betül, and Ülkü Veranyurt. 2021. “Artificial Intelligence in Health Services and Management.” Acta Infologica 5, no. 1: 231-240. https://doi.org/10.26650/acin.750857


Chicago: Humanities Style

Akalın, Betül, and Ülkü Veranyurt. “Artificial Intelligence in Health Services and Management.” Acta Infologica 5, no. 1 (Nov. 2024): 231-240. https://doi.org/10.26650/acin.750857


Harvard: Australian Style

Akalın, B & Veranyurt, Ü 2021, 'Artificial Intelligence in Health Services and Management', Acta Infologica, vol. 5, no. 1, pp. 231-240, viewed 22 Nov. 2024, https://doi.org/10.26650/acin.750857


Harvard: Author-Date Style

Akalın, B. and Veranyurt, Ü. (2021) ‘Artificial Intelligence in Health Services and Management’, Acta Infologica, 5(1), pp. 231-240. https://doi.org/10.26650/acin.750857 (22 Nov. 2024).


MLA

Akalın, Betül, and Ülkü Veranyurt. “Artificial Intelligence in Health Services and Management.” Acta Infologica, vol. 5, no. 1, 2021, pp. 231-240. [Database Container], https://doi.org/10.26650/acin.750857


Vancouver

Akalın B, Veranyurt Ü. Artificial Intelligence in Health Services and Management. Acta Infologica [Internet]. 22 Nov. 2024 [cited 22 Nov. 2024];5(1):231-240. Available from: https://doi.org/10.26650/acin.750857 doi: 10.26650/acin.750857


ISNAD

Akalın, Betül - Veranyurt, Ülkü. “Artificial Intelligence in Health Services and Management”. Acta Infologica 5/1 (Nov. 2024): 231-240. https://doi.org/10.26650/acin.750857



TIMELINE


Submitted30.12.2020
Accepted18.03.2021
Published Online20.04.2021

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