A Growth Artificial Intelligence Algorithm for leNgth and Weight Study
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 250
- 试验地点
- 4
- 主要终点
- Accuracy length AI
研究概览
简要总结
This is a data collection and machine learning accuracy testing project that aims to a) collect training data to enhance, by machine learning, an artificial intelligence (AI) algorithm for measuring length in infants and young children and b) test the accuracy of the AI algorithm by comparing the AI predicted length with the gold standard measured length. Images and videos will be collected by care givers and healthcare professionals, together with physical length measurements. These data will be used to train the AI algorithm and to explore potential improvements. Other data to be collected is user experience feedback.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Other
入排标准
- 年龄范围
- 0 Months 至 24 Months（Child）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Infants/young children aged 0 to 24 months old at enrolment;
- •Caregiver(s) have access to the internet and a smartphone or tablet to complete questionnaires, take images and videos, and upload these;
- •Written informed consent from one or both caregivers (according to local laws) or legally acceptable representative(s) aged ≥ 18 years at enrolment.
排除标准
- •Children unable to undergo length or weight measurements when applying standardized techniques recommended by the WHO (e.g. infants/children with structural abnormalities of the lower limbs or orthopaedic conditions (e.g. club foot, hip dysplasia)).
- •Research staff's uncertainty about the caregiver's ability or willingness to complete the study according to the instructions
研究组 & 干预措施
Children 0-24 months
Children aged 0-24 months of age with no structural abnormalities of the lower limbs or orthopedic conditions
结局指标
主要结局
Accuracy length AI
时间窗: Date of enrolment, at baseline
Accuracy of the Length AI vs length gold standard (WHO methodology with length board in cm) assessed using several different parameters: the bias (cm), agreement and reliability measures, mean absolute error (cm), mean absolute percentage error (%), percentiles of the absolute error (cm), and root mean square error (cm).
Accuracy caregiver length
时间窗: Date of enrolment, at baseline
Accuracy of the caregiver measured length (own preferred methodology in cm) vs gold standard measured length (WHO methodology with length board in cm), assessed by same parameters as mentioned in the first primary outcome measure.
Accuracy caregiver vs AI length
时间窗: Date of enrolment, at baseline
Accuracy of the caregiver measurements (self preferred methodology in cm) vs Length AI by same parameters as mentioned in the first primary outcome measure.
次要结局
- Accuracy weight AI(Date of enrolment, at baseline)
- Ease of use tool(Date of enrolment, at baseline)
- Accuracy caregiver weight(Date of enrolment, at baseline)
- Acceptability tool(Date of enrolment, at baseline)