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

IF 1.5 4区医学 Q3 NURSING Journal of Perinatal & Neonatal Nursing Pub Date : 2024-07-01 Epub Date: 2024-07-29 DOI:10.1097/JPN.0000000000000768

Deniz Yigit, Ayfer Acikgoz

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Abstract

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.

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用人工智能技术评价新生儿舒适行为水平。

背景：新生儿舒适行为量表是评估新生儿舒适度最常用的量表之一。因此，重要的是，通过更实用的评估方法鼓励更多地使用NCBS。目的：本研究旨在设计一种利用人工智能技术评估新生儿舒适度的方法。方法：对某医院新生儿重症监护室362名接受治疗的新生儿进行了基于人工智能的研究。数据收集表格、NCBS和摄像系统被用作数据收集工具。数据采用SPSS Statistics 21.0软件进行分析。采用描述性统计和Cohenκ检验进行分析。结果：研究中提到的两名研究人员首先标记了研究中362名新生儿的视听记录。这些标记的视听记录用于训练（80%）和测试（20%）AI模型。人工智能模型的成功率为99.82%。结论：最终可以看出，所开发的人工智能模型是一种成功的工具，可用于确定新生儿在新生儿重症监护室的舒适行为水平。

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来源期刊

Journal of Perinatal & Neonatal Nursing 医学-妇产科学

CiteScore

1.60

自引率

7.70%

发文量

147

审稿时长

>12 weeks

期刊介绍： The Journal of Perinatal and Neonatal Nursing (JPNN) strives to advance the practice of evidence-based perinatal and neonatal nursing through peer-reviewed articles in a topic-oriented format. Each issue features scholarly manuscripts, continuing education options, and columns on expert opinions, legal and risk management, and education resources. The perinatal focus of JPNN centers around labor and delivery and intrapartum services specifically and overall perinatal services broadly. The neonatal focus emphasizes neonatal intensive care and includes the spectrum of neonatal and infant care outcomes. Featured articles for JPNN include evidence-based reviews, innovative clinical programs and projects, clinical updates and education and research-related articles appropriate for registered and advanced practice nurses. The primary objective of The Journal of Perinatal & Neonatal Nursing is to provide practicing nurses with useful information on perinatal and neonatal nursing. Each issue is PEER REVIEWED and will feature one topic, to be covered in depth. JPNN is a refereed journal. All manuscripts submitted for publication are peer reviewed by a minimum of three members of the editorial board. Manuscripts are evaluated on the basis of accuracy and relevance of content, fit with the journal purpose and upcoming issue topics, and writing style. Both clinical and research manuscripts applicable to perinatal and neonatal care are welcomed.