Classification of medical data using machine-learning techniques
Classification of medical data using machine-learning techniques
Dátum
Szerzők
Dogantimur, Oznur
Shteet, Mahdi
Folyóirat címe
Folyóirat ISSN
Kötet címe (évfolyam száma)
Kiadó
Absztrakt
In our study, detection and estimation of Down Syndrome disease is maintained by analyzing
the serum marker levels measured from the blood samples of the patients as well as the maternal age.
We dealt with a real medical data set provided by Department of Obstetrics and Gynecology of
University of Debrecen. Here, we used supervised learning methods including Logistic Regression
(LR), Support Vector Machine (SVM), Decision Tree (DT), Naive-Bayesian Classification and
Artificial Neural Network (ANN) on a software called RapidMiner Studio[ 3] that is an environment
for designing advanced analytic processes with machine learning, data mining, text mining, predictive
analytic and business analytic. Along with RapidMiner Studio, we used IBM SPSS and Rstudio
softwares to analyze and visualize our medical data set.
Leírás
Kulcsszavak
machine learning, medical data, classification