Diabetes Diagnostic Prediction Using Vector Support Machines.

Procedia Computer Science(2020)

Cited 27|Views0
No score
Abstract
The most important factors for the diagnosis of diabetes mellitus (DM) are age, body mass index (BMI) and blood glucose concentration. Diagnosis of DM by a doctor is complicated, because several factors are involved in the disease, and the diagnosis is subject to human error. A blood test does not provide enough information to make a correct diagnosis of the disease. A vector support machine (SVM) was implemented to predict the diagnosis of DM based on the factors mentioned in patients. The classes of the output variable are three: without diabetes, with a predisposition to diabetes and with diabetes. An SVM was obtained with an accuracy of 99.2% with Colombian patients and an accuracy of 65.6% with a data set of patients of a different ethnic background.
More
Translated text
Key words
Medical Diagnosis,Diabetes Mellitus,Medical Computing,Machine Learning,Vector Support Machines
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined