Skip to main navigation
Skip to search
Skip to main content
WashU Medicine Research Profiles Home
Help & FAQ
Home
Profiles
Departments, Divisions and Centers
Research output
Search by expertise, name or affiliation
Detection of uterine MMG contractions using a multiple change-point estimator and K-means cluster algorithm
P. S. La Rosa
, A. Nehorai
, H. Eswaran
, C. Lowery
, H. Preissl
Department of Electrical & Systems Engineering
Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS)
DBBS - Computational and Systems Biology
DBBS - Neurosciences
DBBS - Biomedical Informatics and Data Science
Institute of Clinical and Translational Sciences (ICTS)
Research output
:
Contribution to journal
›
Article
›
peer-review
1
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Detection of uterine MMG contractions using a multiple change-point estimator and K-means cluster algorithm'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Clustering Algorithm
100%
K-means
100%
Change Point Estimator
100%
Multiple Change-points
100%
During Pregnancy
50%
Root Mean Square
50%
Gestational Age
50%
Segmentation Method
50%
Single Channel
50%
Piecewise Constant
50%
Search Approach
50%
Schwarz Information Criterion
50%
Model-based Segmentation
50%
Binary Search
50%
Zero Mean
50%
Two-stage Detector
50%
Constant Variance
50%
Gaussian Random Variable
50%
Variance Value
50%
Mathematics
K-Means
100%
Point Estimator
100%
Variance
50%
Information Criterion
50%
Mean Square
50%
Gaussian Random Variable
50%
Constant Variance
50%
Gestational Age
50%