对于分散的不完整的纵向行为数据而言,联合的模糊集群
Hieu Ngo1, Hua Fang2, Joshua Rumbut3
1College of Engineering, University of Massachusetts Dartmouth, North Dartmouth, MA, 02747.
概括
这项研究引入了一种新的联合学习算法,用于分析敏感的健康数据,克服行为试验中的隐私和数据复杂性挑战. 这种方法可以实现个性化治疗,同时保护患者的隐私.
科学领域:
- 医疗信息学 医疗信息学
- 机器学习 机器学习
- 数据 隐私 数据 隐私 数据
背景情况:
- 医疗数据分析受到HIPAA等隐私法规的限制.
- 对敏感的健康数据来说,匿名化通常是不够的.
- 传统的集群方法与纵向,不完整的行为健康数据作斗争.
研究的目的:
- 为复杂的纵向行为健康数据开发一个保护隐私的,分散的联合集群算法.
- 解决现有方法在处理缺失数据和跨多站点试验的不同时间点方面的局限性.
主要方法:
- 开发了一种分散的联合多重归因的模糊集群算法.
- 该算法使用联合学习来汇总模型参数,保持数据隐私.
- 它需要最小的通信轮次,并容纳客户有不完整的纵向数据.
主要成果:
- 该算法在集群指标上展示了快速的融合和高性能.
- 对实际的饮食健康数据和具有不同参数的模拟数据集进行了评估.
- 该方法有效地处理来自多站点随机对照试验的复杂纵向数据.
结论:
- 拟议的算法为分析敏感健康数据提供了强大的解决方案,同时确保了患者的隐私.
- 它通过识别行为健康中的患者子组,使得有针对性的治疗成为可能.
- 潜在的应用范围延伸到医疗物联网,用于更广泛的健康数据分析.
关键词:
联合学习是联合学习.医疗事物的互联网, 医疗事物的互联网,行为行为行为.分散式计算是指去中心化的计算.饮食 饮食 饮食 饮食模糊的聚类模糊的聚类.纵向试验是一种纵向试验.缺失的数据 缺失的数据更多相关视频
06:52Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
6.3K
07:12Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Published on: July 1, 2014
12.3K
相关概念视频
Cluster Sampling Method
11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
Behavioral Genetics and Its Designs
363
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
363
Friedman Two-way Analysis of Variance by Ranks
190
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
190
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
69
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
69
Longitudinal Research
12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Longitudinal Studies
157
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
157
