Improvement of the Mouse Grimace Scale set-up for implementing a semi-automated Mouse Grimace Scale scoring (Part 1)

疼痛评估 集合(抽象数据类型) 选择(遗传算法) 人工智能 计算机科学 医学 物理疗法 疼痛管理 程序设计语言
作者
Lisa Ernst,Marcin Kopaczka,Mareike Schulz,Steven R. Talbot,Leonie Zieglowski,Marco Meyer,Stefan Bruch,Dorit Merhof,René H. Tolba
出处
期刊:Laboratory Animals [SAGE Publishing]
卷期号:54 (1): 83-91 被引量:24
标识
DOI:10.1177/0023677219881655
摘要

The Mouse Grimace Scale (MGS) has been widely used for the noninvasive examination of distress/pain in mice. The aim of this study was to further improve its performance to generate repeatable, faster, blinded and reliable results for developing automated and standardized pictures for MGS scoring and simultaneous evaluation of up to four animals. Videos of seven C57BL/6N mice were generated in an experiment to assess pain and stress induced by repeated intraperitoneal injection of carbon tetrachloride (CCl4). MGS scores were taken 1 h before and after the injection. Videotaping was performed for 10 min in special observation boxes. For manual selection, pictures of each mouse were randomly chosen for quality analysis and scored according six quality selection criteria (0 = no, 1 = moderate, 2 = full accordance); the maximum possible score was 12. Overall, 609 pictures from six videos were evaluated for MGS scoring quality; evaluation was performed by using the picture selection tool or by manual scoring. With manual scoring, 288 pictures (48.3% of all randomly generated pictures) were deemed scorable using MGS (mean score = 22.15 ± SD 6.3). To evaluate the algorithm, ratings from different rater groups (beginner, medium-level trained, professional) were compared with the automated image generated. These differences were not significant (p = 0.1091). This study demonstrates an improved set-up and a picture selection tool that can generate repeatable, not-observer biased and standardized pictures for MGS scoring.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
JamesPei应助HA123采纳,获得10
刚刚
猪猪侠完成签到 ,获得积分10
刚刚
1秒前
1秒前
1秒前
2秒前
端庄的寄风完成签到,获得积分10
2秒前
Ava应助拖拉机采纳,获得10
3秒前
3秒前
Sophist发布了新的文献求助10
4秒前
lucky发布了新的文献求助10
4秒前
huoyunli发布了新的文献求助10
5秒前
han发布了新的文献求助10
5秒前
Balance Man发布了新的文献求助10
6秒前
Ava应助文艺点点采纳,获得10
7秒前
量子星尘发布了新的文献求助10
7秒前
AKA蜻蜓队长完成签到,获得积分10
7秒前
二丙完成签到 ,获得积分10
7秒前
Qing发布了新的文献求助10
7秒前
8秒前
8秒前
10秒前
10秒前
10秒前
11秒前
111完成签到,获得积分10
11秒前
夢loey完成签到,获得积分10
11秒前
11秒前
11秒前
11秒前
桐桐应助Sophist采纳,获得10
12秒前
猪猪hero发布了新的文献求助10
12秒前
HA123完成签到,获得积分20
12秒前
珂珂完成签到,获得积分10
13秒前
13秒前
14秒前
打打应助海光采纳,获得10
14秒前
拖拉机发布了新的文献求助10
14秒前
侠女发布了新的文献求助10
14秒前
achenghn发布了新的文献求助10
14秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2700
Neuromuscular and Electrodiagnostic Medicine Board Review 1000
Statistical Methods for the Social Sciences, Global Edition, 6th edition 600
こんなに痛いのにどうして「なんでもない」と医者にいわれてしまうのでしょうか 510
The Insulin Resistance Epidemic: Uncovering the Root Cause of Chronic Disease  500
Walter Gilbert: Selected Works 500
An Annotated Checklist of Dinosaur Species by Continent 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3663010
求助须知:如何正确求助?哪些是违规求助? 3223738
关于积分的说明 9753126
捐赠科研通 2933645
什么是DOI,文献DOI怎么找? 1606294
邀请新用户注册赠送积分活动 758404
科研通“疑难数据库(出版商)”最低求助积分说明 734792