Evaluation of Comfort Behavior Levels of Newborn by Artificial Intelligence Techniques.

BACKGROUND

One of the scales most frequently used in the evaluation of newborn comfort levels is the Neonatal Comfort Behavior Scale (NCBS). It is important therefore that an increased use of the NCBS is encouraged through a more practical method of assessment.

OBJECTIVE

This study was carried out for the purpose of designing a means of assessing neonatal comfort levels by employing the techniques of artificial intelligence (AI).

METHODS

The AI-based study was conducted with 362 newborns under treatment in the neonatal intensive care unit of a hospital. A data collection form, the NCBS, and a camera system were used as data collection tools. The data were analyzed with the SPSS Statistics 21.0 program. Descriptive statistics and Cohen κ test were employed in the analysis.

RESULTS

The 2 researchers named in the study first labeled the audiovisual recordings of the 362 newborns in the study. These labeled audiovisual recordings were used in training (80%) as well as testing (20%) the AI model. The AI model displayed a rate of success of 99.82%.

CONCLUSION

It was ultimately seen that the AI model that had been developed was a successful tool that could be used to determine the comfort behavior levels of newborns in the neonatal intensive care unit.