Prediction of gestational diabetes diagnosis using SVM and J48 classifier model

  title={Prediction of gestational diabetes diagnosis using SVM and J48 classifier model},
  author={Sri Saradha and P. Kola Sujatha},
  journal={International journal of engineering and technology},
  • S. Saradha, P. Sujatha
  • Published 20 April 2018
  • Medicine
  • International journal of engineering and technology
Knowledge Discovery in Databases (KDD) process is also known as data mining. It is a most powerful tool for medical diagnosis. Due to hormonal changes, diabetes may occur during pregnancy is referred as Gestational diabetes mellitus (GDM). Pregnant Women with GDM are at highest risk of future diabetes, especially type-2 diabetes. This paper focuses on designing an automated system for diagnosing gestational diabetes using hybrid classifiers as well as predicting the highest risk factors of… Expand

Tables and Topics from this paper

CSE-DT Features Selection Technique for Diabetes Classification
This paper presents feature selection technique called Classifier Subset Evaluator (CSE) which selects most relevant risk factors for the prevalence of diabetes in the body which attained a better classification accuracy value of 81.64% among others. Expand
A Comparative Study to Predict the Diabetes Risk Using Different Kernels of Support Vector Machine
  • M. Raihan, M. Raihan, L. Akter
  • 2021 2nd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)
  • 2021
Diabetes is a metabolic issue wherein there is an increment in the level of glucose in the blood. The principle explanation behind diabetes is less emission of insulin from the pancreases. After someExpand


Type 2 Diabetes Mellitus Screening and Risk Factors Using Decision Tree: Results of Data Mining
A model using the decision tree for screening T2DM which did not require laboratory tests for T2 DM diagnosis was developed and indicates high capability of the model, especially in identification of the healthy persons. Expand
Design of Hybrid Classifier for Prediction of Diabetes through Feature Relevance Analysis
Data mining plays a major role in the field of clinical data analysis for prediction of many critical diseases. Prediction of diabetes using data mining techniques involves several processes such asExpand
Design and Implementation of Expert Clinical System for Diagnosing Diabetes using Data Mining Techniques
This paper demonstrates creation of expert clinical system for the diagnosis of the diabetic mellitus using clustering and classification techniques of data mining however with suitable modification the same can be extended to evolve similar systems in other application areas in health care. Expand
Comparison of Different Classification Techniques Using WEKA for Hematological Data
The thesis main aims to show the comparison of different classification algorithms using Waikato Environment for Knowledge Analysis or in short, WEKA and find out which algorithm is most suitable for user working on hematological data. Expand
Diabetes affected more than 246 million of people in a worldwide, among a majority of them being women. According to the WHO report, with 2025 this number is expected to grow near or more than 380Expand
Prediction of Heart Diseases and Cancer in Diabetic Patients Using Data Mining Techniques
This work demonstrates the diagnosis of diseases and its importance to predict it earlier and proved this classifiers efficiency for the prediction of heart disease and cancer in diabetic patients. Expand
Diagnosis of diabetes using classification mining techniques
The research hopes to propose a quicker and more efficient technique of diagnosing the disease, leading to timely treatment of the patients, by employing Decision Tree and Naive Bayes algorithms. Expand
Prediction of Diabetes Mellitus using Data Mining Techniques- A Review
This paper concentrates on the overall literature survey related to various data mining techniques for predicting diabetes and would help the researchers to know various datamining algorithm and method for the prediction of diabetes mellitus. Expand
Gestational Diabetes Mellitus: New Diagnostic Criteria
Treatment must be individualized for best results, including a specific diet, physical activity and the use of medications, in face of new evidences regarding their safety and efficacy during pregnancy. Expand
Data Mining Classification Comparison (Naïve Bayes and C4.5 Algorithms)
The author will do a comparison between the performance of the technical classification methods naïve Bayes and C4.5 algorithms. Expand