Introduction The burden of chronic kidney disease (CKD) is growing rapidly around the
world. However, there is limited information on the overall regional prevalence of CKD, as …

The clinical variability between patients with Parkinson's disease (PD) may point at the
existence of subtypes of the disease. Identification of subtypes is important, since a focus on …

Data clustering has been proven to be an effective method for discovering structure in
medical datasets. The majority of clustering algorithms produce exclusive clusters meaning …

Background Cluster analysis (CA) is a frequently used applied statistical technique that
helps to reveal hidden structures and “clusters” found in large data sets. However, this …

It is a great challenge of identification as well as formation of groups of infectious disease
data set. Data mining, a process of uncovering silent characteristics of big data is one of …

In this study, the feasibility of gas chromatography (GC) and gas chromatography–ion
mobility spectrometry (GC–IMS) systems for detecting peanut oil (PO) adulterated with …

The goal of this study is to integrate k-means clustering with data envelopment analysis to
examine technical efficiencies in public hospitals in Turkey. A two-step analysis procedure …

Recent advancement in EHR-based (Electronic Health Record) systems has resulted in
producing data at an unprecedented rate. The complex, growing, and high-dimensional data …

Introduction Distinct motor subtypes of Parkinson's disease (PD) have been described
through both clinical observation and through data-driven approaches. However, the extent …

This study was conducted to develop and evaluate a disability-based classification system
for management of long-term care (LTC) needs in an integrated service delivery system. We …