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.