Yapay Zekâ Destekli Klinik Karar Sistemleri

Çiriş Yıldız C, Başıbüyük M, Yıldırım D. Klinik karar destek sistemlerinin hemşirelikte kullanımı. İnönü Üniv Sağlık Hiz Meslek Yüksekokulu Derg. 2020;8(2):483-495. doi:10.33715/inonusaglik.743296.

Elhaddad M, Hamam S. AI-driven clinical decision support systems: An ongoing pursuit of potential. Cureus. 2024;16(4):e57728. doi:10.7759/cureus.57728.

Tutar Ş, Özgörü H, Şensoy Ö. Pediatri hemşireliğinde yapay zekâ destekli yaklaşımlar. Akdeniz Hemşirelik Derg. 2025;4(3):146-155. doi:10.59398/ahd.1741115.

Cayır A. Hemşirelik eğitiminde yapay zekânın önemi ve yapay zekânın kullanım alanları. Balkan Sağlık Bil Derg. 2025;3(3):187-192. doi:10.61830/balkansbd.1620267.

Rajpurkar P, Chen E, Banerjee O, et al. AI in health and medicine. Nat Med. 2022;28(1):31-38. doi:10.1038/s41591-021-01614-0.

Russell SJ, Norvig P. Artificial intelligence: A modern approach. 4th ed. Hoboken (NJ): Pearson. 2021.

Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-98. doi:10.7861/futurehosp.6-2-94.

Sutton RT, Pincock D, Baumgart DC, et al. An overview of clinical decision support systems. NPJ Digit Med. 2020;3:17.

Gonçalves LS, Amaro MLM, Romero ALM, et al. Implementation of an artificial intelligence algorithm for sepsis detection. Rev Bras Enferm. 2020;73(3):e20180421. doi:10.1590/0034-7167-2018-0421.

Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243. doi:10.1136/svn-2017-000101.

Sendak MP, D’Arcy J, Kashyap S, et al. A path for translation of machine learning products into healthcare delivery. EMJ Innov. 2020;4(1):70-77.

Topol EJ. Deep medicine: How artificial intelligence can make healthcare human again. New York: Basic Books. 2019.

Kelly CJ, Karthikesalingam A, Suleyman M, et al. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019;17(1):195. doi:10.1186/s12916-019-1426-2.

World Health Organization. Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization. 2025.

Ronquillo CE, Peltonen LM, Pruinelli L, et al. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021;77(9):3707-3717. doi:10.1111/jan.14855.

Mikkonen K, Tiainen M, Häggman-Laitila A, et al. Artificial intelligence technologies supporting nurses’ clinical decision-making in healthcare settings: A systematic review. J Adv Nurs. 2025. doi:10.1111/jan.16695.

Tiffen J, Corbridge SJ, Slimmer L. Enhancing clinical decision making. J Prof Nurs. 2014;30(5):399-404. doi:10.1016/j.profnurs.2014.01.011.

Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2018;319(13):1317-1318. doi:10.1001/jama.2017.18391.

Shortliffe EH. Computer-based medical consultations: MYCIN. New York: Elsevier/North-Holland. 1976.

Musen MA, Middleton B, Greenes RA. Clinical decision-support systems. In: Shortliffe EH, Cimino JJ, editors. Biomedical Informatics. London: Springer. 2014: 643-674.

Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-118. doi:10.1038/nature21056.

Singhal K, Tu T, Gottweis J, et al. Towards expert-level medical question answering with large language models. Nature. 2023;620(7972):172-180. doi:10.1038/s41586-023-06291-2.

Tanner CA. Thinking like a nurse: A research-based model of clinical judgment in nursing. J Nurs Educ. 2006;45(6):204-211. doi:10.3928/01484834-20060601-04.

Ekşi Alp E, Türkan D. Çocuk hastalarda sepsis tanı ve tedavisinde güncel yaklaşımlar. Anatolian J Emerg Med. 2024;7(4):182-189. doi:10.54996/anatolianjem.1604382.

De Souza DC, Gonçalves Martin J, Soares Lanziotti V, et al. The epidemiology of sepsis in paediatric intensive care units in Brazil (SPREAD PED): an observational study. Lancet Child Adolesc Health. 2021;5(12):873-881. doi:10.1016/S2352-4642(21)00286-8.

Heming N, Azabou E, Cazaumayou X, et al. Sepsis in the critically ill patient: Current and emerging management strategies. Expert Rev Anti Infect Ther. 2021;19(5):635-647. doi:10.1080/14787210.2021.1846522.

Khosravi M, Zare Z, Mojtabaeian SM, et al. Artificial intelligence and decision-making in healthcare: A thematic analysis of a systematic review of reviews. Health Serv Res Manag Epidemiol. 2024;11:23333928241234863. doi:10.1177/23333928241234863.

Padula WV, Delarmente BA. The national cost of hospital-acquired pressure injuries in the United States. Int Wound J. 2019;16(3):634-640. doi:10.1111/iwj.13071.

Shim S, Yu JY, Jekal S, et al. Development and validation of interpretable machine learning models for inpatient fall events and electronic medical record integration. Clin Exp Emerg Med. 2022;9(4):345-353. doi:10.15441/ceem.22.354.

Gerich HV, Moen H, Block LJ, et al. Artificial intelligence-based technologies in nursing: A scoping literature review of the evidence. Int J Nurs Stud. 2022;127:104153. doi:10.1016/j.ijnurstu.2021.104153.

Kamal K. Yapay zekâ destekli klinik karar destek sistemlerinin tanı doğruluğuna etkisi (yüksek lisans tezi). İstanbul: İstanbul Okan Üniversitesi. 2026.

Robert N. How artificial intelligence is changing nursing. Nurs Manage. 2019;50(9):30-39. doi:10.1097/01.NUMA.0000578988.56622.21.

Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347-1358. doi:10.1056/NEJMra1814259.

Obermeyer Z, Powers B, Vogeli C, et al. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447-453. doi:10.1126/science.aax2342.

Goddard K, Roudsari A, Wyatt JC. Automation bias: A systematic review of frequency, effect mediators, and mitigators. J Am Med Inform Assoc. 2012;19(1):121-127. doi:10.1136/amiajnl-2011-000089.

Keskinbora KH. Medical ethics considerations on artificial intelligence. J Clin Neurosci. 2019;64:277-282. doi:10.1016/j.jocn.2019.03.001.

Samek W, Montavon G, Lapuschkin S, et al. Explaining deep neural networks and beyond: A review of methods and applications. Proc IEEE. 2021;109(3):247-278. doi:10.1109/JPROC.2021.3060483.

Corral-Acero J, Margara F, Marciniak M, et al. The digital twin to enable the vision of precision cardiology. Eur Heart J. 2020;41(48):4556-4564. doi:10.1093/eurheartj/ehaa159.

Özdemir Z. Meme kanseri hastalarında yapay zekâ destekli karar sistemlerinin sonuçlarının multidisipliner meme kanseri konsey kararları ile karşılaştırılması (tıpta uzmanlık tezi). İstanbul: İstanbul Üniversitesi-Cerrahpaşa.2026.