Artificial Intelligence and Machine Learning Applications in Pain Assessment of Pediatric Patients
Pediatri hastalarının ağrı değerlendirmesinde hemşirelerin yapay zekâ ve makine öğrenimi uygulamaları
Artificial intelligence is a transformational technology affecting healthcare. With the emergence of artificial intelligence, revolutionary innovations have occurred in defence, finance, communication and healthcare. The use of artificial intelligence and machine learning in the health field; data analysis and integration of data into health services facilitate the adoption of technology by health professionals in diagnosis, treatment and patient care. Many interventions applied in the hospital and hospitalisation, which is the environment where healthcare services are provided, can cause fear, pain, anxiety and trauma in pediatric patients. Therefore, it is necessary to reduce the stress factors caused by illness and hospitalisation in newborns and children and to minimise these traumatic experiences. In addition to pharmacological methods, non-pharmacological methods are also used during the implementation of painful clinical procedures. Non-pharmacological methods are effective in reducing the rate of analgesic use, eliminating or reducing pain problems, and improving patients' quality of life. Non-pharmacological methods used in pain control of pediatric patients include behavioural, cognitive, combined cognitive-behavioural, physical and emotional approaches. As a non-pharmacological method, artificial intelligence, which has been widely used in the field of medicine in recent years, helps health professionals shape their practices, and its use is becoming increasingly important. With the use of artificial intelligence assessment tools and machine learning, more objective assessment results will be obtained in pain assessment, nurse workload will decrease and thus the time allocated for care will increase. In this context, this review aims to investigate the results of studies on the effect of artificial intelligence and machine learning applications in pain assessment of pediatric patients.
Yapay zekâ, sağlık hizmetini etkileyen dönüşümsel bir teknolojidir. Yapay zekanın ortaya çıkışı ile savunma, finans, iletişim ve sağlık alanında devrim niteliğinde yenilikler meydana gelmiştir. Yapay zekâ ve makine öğreniminin sağlık alanında kullanımı; veri analizi ve verilerin sağlık hizmetlerine entegrasyonu, tanı, tedavi ve hasta bakımında sağlık profesyonellerinin teknolojiyi benimsemelerini kolaylaştırmaktadır. Sağlık hizmetinin sunulduğu ortam olan hastane ve hastaneye yatışta uygulanan birçok girişim; pediatri hastalarında korku, ağrı, anksiyete ve travmaya neden olabilmektedir. Dolayısıyla yenidoğanlarda ve çocuklarda hastalık ve hastaneye yatışın neden olduğu stres faktörlerinin azaltılması ve bu travmatik deneyimlerin en aza indirilmesi gerekmektedir. Ağrılı klinik prosedürlerin uygulanması sırasında farmakolojik yöntemlerin yanı sıra non-farmakolojik yöntemler de kullanılmaktadır. Non-farmakolojik yöntemler; analjezik kullanma oranını azaltma, ağrı problemini giderme ya da azaltma ve hastaların yaşam kalitesini arttırmada etkilidir. Pediatri hastalarının ağrı kontrolünde kullanılan non-farmakolojik yöntemler; davranışsal, bilişsel, birleşik bilişsel-davranışsal, fiziksel ve duygusal yaklaşımları içeren yöntemlerdir. Non-farmakolojik bir yöntem olarak son yıllarda tıp alanında kullanımı oldukça yaygınlaşan yapay zekâ, sağlık çalışanlarının uygulamalarının şekillenmesi aşamasında sağlık profesyonellerine yardımcı olmakta ve kullanımı giderek önem kazanmaktadır. Yapay zekâ değerlendirme araçlarının ve makine öğreniminin kullanılması ile ağrıyı değerlendirmede daha objektif değerlendirme sonuçları ortaya çıkacak, hemşire iş yükü azalacak ve böylece bakım için ayrılan sürede artış olacaktır. Bu bağlamda bu derlemenin amacı; pediatri hastalarının ağrı değerlendirmelerinde hemşirelerin yapay zekâ ve makine öğrenimi uygulamalarının etkisine ilişkin çalışmaların sonuçlarını araştırmaktır.
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- Makale Türü Derleme Makalesi
- Gönderildi Ağustos 29, 2024
- Yayınlanmış Ağustos 31, 2025
- Sayı Cilt 5 Sayı 2 (2025): Journal of Infant, Child and Adolescent Health
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