Endometriyum Kanserinin Bakım ve Yönetiminde Yapay Zeka

Yıl 2024, Sayı: 10, 38 - 46, 23.12.2024

Oya Kavlak , Ruken Yağız Altıntaş

https://doi.org/10.58252/artukluhealth.1497539

Öz

Endometriyum kanseri, ülkemizde jinekolojik kanserler arasında birinci sırada yer almaktadır ve erken teşhisi, hastalığın prognozu açısından kritik öneme sahiptir. Günümüzde, bu kanser türünün bakım ve yönetiminde cerrahi yöntemler, kemoterapi, radyoterapi ve hormon tedavileri gibi birçok yenilikçi yaklaşım ve teknoloji kullanılmaktadır. Son yıllarda, yapay zeka teknolojilerinin sağlık alanındaki kullanımı hızla artmış olup, endometriyum kanserinin erken teşhisinde, prognostik değerlendirmelerde ve tedavi planlamasında önemli avantajlar sunmaktadır. Yapay zeka teknolojisi, endometriyum kanseri bakımında hemşirelik uygulamalarını çeşitli şekillerde iyileştirebilir ve geliştirebilir. Uzaktan izleme ve bakım kolaylığı sağlayarak hastaların durumu daha yakından takip ve gerektiğinde hızlı müdahale etmesine olanak tanımaktadır. Hata oranlarının azalması ve maliyetlerin düşmesi, hemşirelik bakımında daha güvenilir ve ekonomik çözümler sunabilmektedir. Hemşirelik bakımında karar alma ve risk değerlendirmesi süreçlerinde yapay zekanın sunduğu analiz ve tahminler, hemşirelerin daha doğru ve etkili kararlar almasını sağlayabilmektedir. Ayrıca, yapay zeka teknolojileri iş yükünü azaltarak hemşirelerin hastalara daha fazla odaklanmasına ve daha kaliteli bakım sunmasına fırsat tanımaktadır. Ancak, bu faydaların tam olarak gerçekleştirilmesi için veri önyargısı, gizlilik, düzenleme ve etikle ilgili zorluklar da ele alınmalıdır. Yapay zeka teknolojilerinin etik kurallara uygun ve doğru bir şekilde kullanılması, sağlık alanındaki geleceği şekillendirmede önemli bir rol sahip olacaktır.

Anahtar Kelimeler

Endometriyum kanseri, Hemşirelik, Bakım, Yapay Zeka

Etik Beyan

derleme makale olduğu için etik kurul izni gereksizdir. Yazarlar çıkar çatışması beyan etmemeişlerdir.

Artificial Intelligence in the Care and Management of Endometrial Cancer

Öz

Endometrial cancer is the most common gynecological cancer in our country, and early diagnosis is crucial for the prognosis of the disease. Nowadays, various innovative approaches and technologies are used in the care and management of this cancer type, including surgical methods, chemotherapy, radiotherapy, and hormone therapies. In recent years, the use of artificial intelligence technologies in the healthcare field has rapidly increased, providing significant advantages in the early diagnosis, prognostic evaluations, and treatment planning of endometrial cancer. Artificial intelligence technology can improve and enhance nursing practices in endometrial cancer care in various ways. It enables closer monitoring of patients' conditions through remote monitoring and care, allowing for timely interventions when necessary. The reduction of error rates and costs offers more reliable and economical solutions in nursing care. In the decision-making and risk assessment processes of nursing care, the analyses and predictions provided by artificial intelligence help nurses make more accurate and effective decisions. Additionally, artificial intelligence technologies reduce the workload, allowing nurses to focus more on patients and provide higher-quality care. However, to fully realize these benefits, challenges related to data bias, privacy, regulation, and ethics must also be addressed. The correct and ethical use of artificial intelligence technologies will have an important role in shaping the future in healthcare.

Anahtar Kelimeler

Endometrial cancer, Nursing, Care, Artificial intelligence

Kaynakça

• American College of Obstetricians and Gynaecologists (ACOG), (2015). Endometrial cancer. https://www.acog.org/clinical/clinical-guidance/practice-bulletin/articles/2015/04/endometrial-cancer adresinden 30 Nisan 2024 tarihinde alınmıştır.
• American Cancer Society (ASC), (2024). Key Statistics for Endometrial Cancer. https://www.cancer.org/cancer/types/endometrial-cancer/about/key-statistics.html adresinden 17 Aralık 2024 tarihinde alınmıştır.
• Ateş, F.F., Çalışkan, A. ve Toğaçar, M. (2022). Meme kanserinin tespiti için yapay zeka tabanlı hibrit bir model önerisi. Fırat Üniversitesi Fen Bilimleri Dergisi, 34(2), 189-199.
• Akazawa, M. and Hashimoto, K. (2021). Artificial intelligence in gynecologic cancers: current status and future challenges–a systematic review. Artificial Intelligence in Medicine, 120, 102164. https://doi.org/10.1016/j.artmed.2021.102164
• Amant, F., Mirza, M.R., Koskas, M. and Creutzberg, C.L. (2018). Cancer of the corpus uteri. International Journal of Gynecology & Obstetrics, 143, 37-50. https://doi.org/10.1002/ijgo.12612
• Astromskė, K., Peičius, E. and Astromskis, P. (2021). Ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations. AI & Society, 36(2), 509-520. https://doi.org/10.1007/s00146-020-01008-9
• Bilge, Ç. ve Akdolun Balkaya, N. (2022). Endometrium kanseri ve hemşirelik bakımı. Jinekolojik onkolojide bakım (1. Baskı, s.261-286) içinde. Akademisyen Kitabevi.
• Bilge, Ç., Kaydırak, M.M. ve Aslan, E. (2016). Jinekolojik kanserin cinsel yaşam üzerindeki etkileri. Süleyman Demirel Üniversitesi Sağlık Bilimleri Dergisi, 7(3), 31-38.
• Bradford, L.S., Rauh-Hain, J.A., Schorge, J., Birrer, M.J. and Dizon, D.S. (2015). Advances in the management of recurrent endometrial cancer. American Journal of Clinical Oncology, 38(2), 206-212 https://doi.org/10.1097/COC.0b013e31829a2974
• Becker, A. (2019). Artificial intelligence in medicine: What is it doing for us today?. Health Policy Technol, 8,198–205. https://doi.org/10.1016/j.hlpt.2019.03.004
• Carroll, W. (2018). Artificial intelligence, nurses and the quadruple aim. Online Journal of Nursing Informatics, 22(2).
• Constantine, G.D., Kessler, G., Graham, S. and Goldstein, S.R. (2019). Increased incidence of endometrial cancer following the women's health initiative: an assessment of risk factors. J Womens Health (Larchmt), 28, 237-243. https://doi.org/10.1089/jwh.2018.6956
• Concin, N., Matias-Guiu, X., Vergote, I., Cibula, D., Mirza, M.R., Marnitz, S., ... Creutzberg, C.L. (2021). ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma. International Journal of Gynecologic Cancer, 31(1), 12-39. https://doi/10.1136/ijgc-2020-002230
• Cote, M.L., Ruterbusch, J.J., Olson, S.H., Lu, K. and Ali-Fehmi, R. (2015). The growing burden of endometrial cancer: a major racial disparity affecting black women. Cancer Epidemiol Biomarkers Prev, 24(9),1407-1415. https://doi/10.1158/1055-9965.EPI-15-0316
• DeStephano, C.C., Bakkum-Gamez, J.N., Kaunitz, A.M., Ridgeway, J.L. and Sherman, M.E. (2020). Intercepting endometrial cancer: Opportunities to expand access using new technology. Cancer Prevention Research, 13(7), 563-568. https://doi/10.1158/1940-6207.CAPR-19-0556
• Doğan, F. ve Türkoğlu, İ. (2019). Derin öğrenme modelleri ve uygulama alanlarına ilişkin bir derleme. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, 10(2), 409-445. https://doi.org/10.24012/dumf.411130
• Edmonds, J.K. (2023). Use of artificial ıntelligence to ımprove women’s health and enhance nursing care. Journal of Obstetric, Gynecologic & Neonatal Nursing, 52(3), 169-171. https://doi/10.1016/j.jogn.2023.03.004
• Erdemoğlu, E., Serel, T.A., Karacan, E., Köksal, O.K., Turan, İ., Öztürk, V. and Bozkurt, K.K. (2023). Artificial intelligence for prediction of endometrial intraepithelial neoplasia and endometrial cancer risks in pre-and postmenopausal women. AJOG Global Reports, 3(1), 100154. https://doi.org/10.1016/j.xagr.2022.100154
• Ferlay, J., Soerjomataram, I., Dikshit, R., Eser, S., Mathers, C., Rebelo, M., Parkin, D.M., Forman, D. and Bray, F. (2015). Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer, 136:E359–86. https://doi.org/10.1002/ijc.29210
• Globocan International Agency for Research on Cancer 2022. Global Cancer Observatory: Cancer Today. (2022). https://gco.iarc.fr/today/en/dataviz/pie?mode=cancer&sexes=2&cancers=24&group_populations=1&populations=900 adresinden 30 Nisan 2024 tarihinde alınmıştır.
• Gombolay, M., Yang, X.J., Hayes, B., Seo, N., Liu, Z., Wadhwania, S. and Shah, J. (2018). Robotic assistance in the coordination of patient care. International Journal of Robotics Research, 37(10), 1300–1316. https://doi.org/10.1177/0278364918778344
• Gökçü, M., Erkılınç, S., Solmaz, U., Bağcı, M., Temel, O., Karadeniz, T. ve Sancı, M. (2018). Yüksek riskli ve düşük riskli endometrium kanserleri hastalarda ileri yaş kötü prognostik bir faktör müdür?. Bozok Tıp Dergisi, 8(3), 99-108. https://doi.org/10.16919/bozoktip.373914
• Günakan, E., Atan, S., Haberal, A.N., Küçükyıldız, İ.A., Gökçe, E. ve Ayhan, A. (2019). A novel prediction method for lymph node involvement in endometrial cancer: Machine learning. International Journal of Gynecologic Cancer, 29(2). https://doi.org/10.1136/ijgc-2018-000033
• Henley, S.J., Miller, J.W., Dowling, N.F., Benard, V.B. and Richardson, L.C. (2018). Uterine cancer incidence and mortality United States, 1999-2016. MMWR. Morbidity and mortality weekly report, 67.https://doi.org/10.15585/mmwr.mm6748a1
• Jiang, F., Jiang, Y., Zhi H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q. and Shen, H. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol, 2,230. https://doi.org/10.1136/svn-2017-000101.
• Kaya, U., Yılmaz, A. ve Dikmen, Y. (2019). Sağlık alanında kullanılan derin öğrenme yöntemleri. Avrupa Bilim ve Teknoloji Dergisi, 16, 792-808. https://doi.org/10.31590/ejosat.573248
• Koh, W.J., Abu-Rustum, N.R., Bean, S., Bradley, K., Campos, S.M., Cho, K.R., ... Scavone, J. L. (2018). Uterine neoplasms, version 1.2018, NCCN clinical practice guidelines in oncology. Journal of the National Comprehensive Cancer Network, 16(2), 170-199. https://doi.org/10.6004/jnccn.2018.0006
• Korytnikova, E. (2023). Artificial intelligence and women's health: innovations, challenges, and ethical considerations. Adv Clin Med Res, 4(3),1-6. https://doi.org/10.52793/ACMR.2023.4(3)-59
• Locsin, R.C. (2016). Technological competency as caring in nursing: co-creating moments in nursing occurring within the universal technological domain. Journal of Theory Construction Testing, 20(1), 5-11. https://doi.org/10.2478/sjph-2022-0016
• Makker, V., Green, A.K., Wenham, R.M., Mutch, D., Davidson, B. and Miller, D.S. (2017). New therapies for advanced, recurrent, and metastatic endometrial cancers. Gynecologic Oncology Research and Practice, 4(19), 1-12. https://doi.org/10.1186/s40661-017-0056-7
• Martinez-Ortigosa, A., Martinez-Granados, A., Gil-Hernández, E., Rodriguez-Arrastia, M., Ropero-Padilla, C. And Roman, P. (2023). Applications of artificial ıntelligence in nursing care: a systematic review. Journal of Nursing Management, 1-12. https://doi.org/10.1155/2023/3219127
• Mysona, D.P., Tran, L.K.H., Tran, P.M.H., Gehrig, P.A., Van Le, L., Ghamande, S., ... Chan, J.K. (2020). Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers. Gynecol Oncol, 156(1),77–84. https://doi.org/10.1016/j.ygyno.2019.10.017
• National Cancer Institute (NIH), (2024). Surveillance, Epidemiology, and End Results Program (SEER), Cancer Stat Facts: Uterine Cancer. https://seer.cancer.gov/statfacts/html/corp.html adresinden 30 Nisan 2024 tarihinde alınmıştır.
• Neofytou, M.S., Tanos, V., Constantinou, I., Kyriacou, E. C., Pattichis, M.S. and Pattichis, C.S. (2015). Computer-aided diagnosis in hysteroscopic imaging. IEEE Journal of Biomedical and Health Informatics, 19(3), 1129-1136. https://doi.org/10.1109/JBHI.2014.2332760
• Obermeyer, Z., Powers, B., Vogeli, C. and Mullainathan, S. (2019) Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464),447-453. https://doi.org/10.1126/science.aax2342
• O'Connor, S., Yan, Y., Thilo, F.J., Felzmann, H., Dowding, D. and Lee, J.J. (2023). Artificial intelligence in nursing and midwifery: A systematic review. Journal of Clinical Nursing, 32(13-14), 2951-2968. https://doi.org/10.1111/jocn.16478
• Özlen, T. ve Güneş, A. (2021). Servikal kanserlerin teşhisinde kullanılan makine öğrenmesi algoritmalarının karşılaştırmalı analizi. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 21(5), 1052-1060. https://doi.org/10.35414/akufemubid.861575
• Pailaha, A.D. (2023). The impact and issues of artificial intelligence in nursing science and healthcare settings. SAGE Open Nursing, 9, 1-4. https://doi.org/10.1177/23779608231196847
• Passarello, K., Kurian, S. and Villanueva, V. (2019). Endometrial cancer: an overview of pathophysiology, management, and care. Seminars in Oncology Nursing, 35(2), 157-165. https://doi.org/10.1016/j.soncn.2019.02.002
• Pergialiotis, V., Pouliakis, A., Parthenis, C., Damaskou, V., Chrelias, C., Papantoniou N. and Panayiotides, I. (2018). The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women. Public Health, 164,1–6. https://doi.org/10.1016/j.puhe.2018.07.012
• Reddy Allan, S., Coghlan, S. and Cooper, P. (2020). A governance model for the application of AI in health care. Journal of the American Medical Informatics Association. 27(3), 491-497. https://doi.org/10.1093/jamia/ocz192
• Salman, T. ve Dinçkal, Ç. (2022). Kanser ve immünoterapi, sağlık biyoteknolojisi. (1. Baskı, s. 78-84). Ankara: Türkiye Klinikleri.
• Schwalbe, N. and Wahl, B. (2020). Artificial intelligence and the future of global health. The Lancet, 395(10236), 1579-1586. https://doi.org/10.1016/S0140-6736(20)30226-9
• Seibert, K., Domhoff, D., Bruch, D., Schulte-Althoff, M., Fürstenau, D., Biessmann, F. and Wolf-Ostermann, K. (2021). Application scenarios for artificial intelligence in nursing care: Rapid review. Journal of Medical Internet Research, 23(11), e26522. https://doi.org/10.2196/26522
• Smrz, S.A., Calo, C., Fisher, J.L. and Salani, R. (2021). An ecological evaluation of the increasing incidence of endometrial cancer and the obesity epidemic. Am J Obstet Gynecol, 224(5), 506.e1-506.e8. https://doi.org/10.1016/j.ajog.2020.10.042
• Solmaz, U., Ekin, A., Mat, E., Dereli, L., Gezer, C., Gökçü, M., Ayaz, D. ve Sancı, M. (2016). Endometriyum kanserinde güncel yaklaşımlar. Türk Jinekolojik Onkoloji Dergisi, 19(1), 7-16.
• Thomasian, M.N., Eickhoff, C. and Adashi, E.Y. (2021). Advancing health equity with artificial intelligence. J Public Health Policy. 42(4), 602-611. https://doi.org/10.1057/s41271-021-00319-5
• Tran, A.Q. and Gehrig, P. (2017). Recent advances in endometrial cancer. F1000Research, 6, 81-85. https://doi.org/10.12688/f1000research.10020.1
• Wang, R., Pan, W., Jin, L., Li, Y., Geng, Y., Gao, C., Chen, G., Wang, H., Ma, H.D. ve Liao, S. (2019). Artificial intelligence in reproductive medicine. Reproduction, 158(4), R139-R154. https://doi.org/10.1530/REP-18-0523
• Wu, S.F., Tong, H.Y., Kan, Y.Y., Su, S.H., Lee, M.C., Kao, C.C. and Lin, Y.H. (2017). The exploration of health-related quality of life: factors influencing quality of life in gynecologic cancer patients. Clinical Nursing Research, 26(1), 114-131. https://doi.org/10.1177/1054773815600665
• Yan, B.C., Li, Y., Ma, F.H., Zhang, G.F., Feng, F., Sun, M.H., Lin, W.G. and Qiang, J.W. (2021). Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study. European Radiology, 31(1), 411-422. https://doi.org/10.1007/s00330-020-07099-8
• Yoldemir, T. (2020) Artificial intelligence and women’s health. Climacteric, 23(1), 1-2, https://doi.org/10.1080/13697137.2019.1682804
• Vanderstraeten, A., Tuyaerts, S. and Amant, F. (2015). The immune system in the normal endometrium and implications for endometrial cancer development. Journal of Reproductive Immunology, 109, 7-16. https://doi.org/10.1016/j.jri.2014.12.006
• Vezzoli, M., Ravaggi, A., Zanotti, L., Miscioscia, R.A., Bignotti, E., Ragnoli, M., Gambino, A., Ruggeri, G., Calza, S., Sartori, E. and Odicino, F. (2017). RERT: a novel regression tree approach to predict extrauterine disease in endometrial carcinoma patients. Scientific Reports, 7(1), 10528. https://doi.org/10.1038/s41598-017-11104-4