Multi-Dimensional Validation of the Integration of Syntactic and Semantic Distance Measures for Clustering Fibromyalgia Patients in the Rheumatic Monitor Big Data Study

Multi-Dimensional Validation of the Integration of Syntactic and Semantic Distance Measures for Clustering Fibromyalgia Patients in the Rheumatic Monitor Big Data Study

This study primarily aimed at developing a novel multi-dimensional methodology to discover and validate the optimal number of clusters. The secondary objective was to deploy it for the task of clustering fibromyalgia patients. We present a comprehensive methodology that includes the use of several d...

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Bibliographic Details
Main Authors: Ayelet Goldstein, Yuval Shahar, Michal Weisman Raymond, Hagit Peleg, Eldad Ben-Chetrit, Arie Ben-Yehuda, Erez Shalom, Chen Goldstein, Shmuel Shay Shiloh, Galit Almoznino
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Bioengineering
Subjects:
cluster analysis
machine learning algorithm
K-means
Big Data
fibromyalgia
rheumatic diseases
Online Access:https://www.mdpi.com/2306-5354/11/1/97

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