从婴儿健康记录中预测自闭症特征:一种机器学习方法
Ayelet Ben-Sasson1, Joshua Guedalia1, Keren Ilan1
1University of Haifa, Israel.
概括
早期识别自闭症谱状况 (ASC) 对于干预至关重要. 一个新的模型使用婴儿健康访问记录从前两年来预测ASC的可能性,帮助男孩和女孩的早期检测.
科学领域:
- 发育儿科 发育儿科
- 计算健康 计算健康
- 公共卫生 公共卫生
背景情况:
- 早期识别自闭症谱状况 (ASC) 对有效干预至关重要.
- 常规的健康数据为检测ASC早期指标提供了潜力.
- 技术进步促进了对发育查的新方法.
研究的目的:
- 开发和测试一个自闭症谱状况 (ASC) 可能性的预测模型,使用例行收集的婴儿健康访问记录.
- 评估模型在在生命的前两年内识别儿童的ASC的表现.
- 通过使用健康记录,探索早期ASC检测中的性别特异性模式.
主要方法:
- 通过使用2岁以下儿童婴儿健康访问的电子健康记录开发了一个预测模型.
- 这项研究包括一个庞大的队列:591,989名非自闭症儿童和12,846名被诊断为ASC的儿童.
- 评估了模型性能以确定ASC,分析考虑了性别特异性差异.
主要成果:
- 该模型确定了三分之二的儿童患有ASC (63%的男孩,66%的女孩).
- 关键的预测特征包括语言,精细运动和社会里程碑 (12-24个月),产妇年龄和生长模式.
- 父母对发育或听力方面的担忧是重要的预测因素,以及模型之间的出生和生长参数的差异.
结论:
- 在生命的头两年内例行收集的健康数据可以用来支持早期自闭症谱状况 (ASC) 检测.
- 已开发的模型在识别男孩和女孩的ASC早期症状方面表现有前途.
- 这些发现支持将预测分析集成到标准儿科护理中,以便及时识别和干预ASC.
相关概念视频
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
01:19Autism Spectrum Disorder
83
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by persistent deficits in social communication and interaction alongside restrictive and repetitive behaviors or interests. ASD is sometimes accompanied by intellectual impairment.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
83
01:18Steps in Outbreak Investigation
123
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
123