Prediction of systemic lupus erythematosus based on cutaneous manifestations using machine learning models
S Samundeswari, V Ramalingam, B Latha and S Palanivel
Systemic Lupus Erythematosus (SLE) or Lupus is an auto immune system in which the human insusceptible framework ends up plainly hyperactive and affects typical, solid tissues. Diagnosing the lupus is troublesome and the specialist may set aside long opportunity to analyze this intricate sickness precisely. This experimental study made utilization of images gathered from various hospitals in Tamilnadu. Images of 400 patients (200 SLE and 200 normal) are taken into this study. Machine learning models can offer a help to the doctor to predict the disease at the early stage early stage itself. Three classifiers, Naïve Bayes, Multilayer perceptron (MLP) and Random Forest are considered to classify the patients. Experimental results demonstrate that the MLP gives higher accuracy than different models for recognizing SLE.
How to cite this article:
S Samundeswari, V Ramalingam, B Latha, S Palanivel. Prediction of systemic lupus erythematosus based on cutaneous manifestations using machine learning models. Pharma Innovation 2017;6(10):248-251.