K-Means is one of the major algorithms widely used in clustering due to its good
computational performance. However, K-Means is very sensitive to the initially selected …

Rough set theory (RST) was proposed as a mathematical tool to deal with the analysis of
imprecise, uncertain or incomplete information or knowledge. It is of fundamental importance …

Background: Timely diagnosis of post-intubation tracheal stenosis (PITS), which is one of the
most serious complications of endotracheal intubation, may change its natural history. To …

Abstract Machine learning and other artificial intelligence techniques have been extensively
used in a large number of medical applications, in diagnosis, treatment selection, mining of …

The purpose of this study was to examine the changes in voice onset time (VOT) of stroke
patients (elderly) and healthy elderly, and to compare them. Also, to propose a prediction …

Background and purpose Machine learning (ML) has attracted much attention with the hope
that it could make use of large, routinely collected datasets and deliver accurate …

The epidemiological question of concern here is “can young children at risk of obesity be
identified from their early growth records?” Pilot work using logistic regression to predict …

Over 1.25 million people are killed, and 20-50 million people are seriously impacted by road
traffic injuries on earth every year according to the world bank. This dissertation aims to the …

Disease diagnosis system in medicine is a peculiar form of clinical data processing coming
from a range of clinical as well as atomized systems. However, it is more complicated in …

The objective of this study was to conduct a systematic review of applications of data mining
techniques in the field of stroke research. We searched the MEDLINE database through …