Logo
  • Home
  • About Us
    • Aim and Scope
    • Research Area
    • Impact Factor
    • Indexing
  • For Authors
    • Authors Guidelines
    • How to publish paper?
    • Download Paper format
    • Submit Manuscript
    • Processing Charges
    • Download Copyrights Form
    • Submit Payment-Copyrights
  • Archives
    • Current Issues
    • Past Issues
    • Conference Issues
    • Special Issues
    • Advance Search
  • IJARIIE Board
    • Join as IJARIIE Board
    • Advisory Board
    • Editorial Board
    • Sr. Reviewer Board
    • Jr. Reviewer Board
  • Proposal
    • Conferece Proposal
    • Special Proposal
    • Faqs
  • Contact Us
  • Payment Detail

Call for Papers:Vol.11 Issue.4

Submission
Last date
28-Aug-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-4. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

  • How to Publish Paper
  • Submit Manuscript
  • Processing Charges
  • Submit Payment

Archives

  • Current Issue
  • Past Issue

IJARIIE Board

  • Member Of Board
  • Join As Board

Downloads

  • Authors Guidelines
  • Manuscript Template
  • Copyrights Form

Android App

Download IJARIIE APP
  • Authors
  • Abstract
  • Citations
  • Downloads
  • Similar-Paper

Authors

Title: :  Fetal Health Classification based on CTG using Machine learning
PaperId: :  20212
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 3 2023
DUI:    16.0415/IJARIIE-20212
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Radhika Vinod AgarwalBangalore Institute of technology
Akansha KediaBangalore Institute of technology
Yusra Naheed Bangalore Institute of technology
Sanjitha NBangalore Institute of technology
Manasa T PBangalore Institute of technology

Abstract

Computer science and engineering
Fetal health, Cardiotocography, Classification
The UN has estimated that 24 million babies were born in India in 2017 and 35,000 mothers died during or shortly after birth, with MMR at 145 per 100,000 live births, or 12% of parental deaths worldwide. Classification of fetal health is an important aspect of child care and can help prevent negative consequences. Cardiotocography (CTG) is a method often used to monitor fetal health, but its interpretation can be subjective and inaccurate. In recent years, machine learning methodologies and techniques have been proposed as a solution for improvement in the accuracy of CTG-based classification of fetus. In this study, we developed a classifier that automatically predicts fetal health using different learning machines. We used a database of CTG data from the University of California, Irvine's Machine Learning Repository containing 2126 subjects and 21 features, including 1655 healthy subjects, 295 unhealthy subjects and pathologically diseased there are 176 subjects. The proposed model has the potential to improve the accuracy and purpose of CTG-based fetal health classification, leading to better prenatal care and better outcomes for mothers and foetuses. As a comparison, the best model for prediction is random forest with 96% accuracy.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. "Fetal Health Classification based on CTG using Machine learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 3 2023 Page 1177-1182
MLA Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. "Fetal Health Classification based on CTG using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education 9.3(2023) : 1177-1182.
APA Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, & Manasa T P. (2023). Fetal Health Classification based on CTG using Machine learning. International Journal Of Advance Research And Innovative Ideas In Education, 9(3), 1177-1182.
Chicago Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. "Fetal Health Classification based on CTG using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 3 (2023) : 1177-1182.
Oxford Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. 'Fetal Health Classification based on CTG using Machine learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, 2023, p. 1177-1182. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Fetal_Health_Classification_based_on_CTG_using_Machine_learning_ijariie20212.pdf (Accessed : 26 November 2024).
Harvard Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. (2023) 'Fetal Health Classification based on CTG using Machine learning', International Journal Of Advance Research And Innovative Ideas In Education, 9(3), pp. 1177-1182IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Fetal_Health_Classification_based_on_CTG_using_Machine_learning_ijariie20212.pdf (Accessed : 26 November 2024)
IEEE Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P, "Fetal Health Classification based on CTG using Machine learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, pp. 1177-1182, May-Jun 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Fetal_Health_Classification_based_on_CTG_using_Machine_learning_ijariie20212.pdf [Accessed : 26 November 2024].
Turabian Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. "Fetal Health Classification based on CTG using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 3 (26 November 2024).
Vancouver Radhika Vinod Agarwal, Akansha Kedia, Yusra Naheed , Sanjitha N, and Manasa T P. Fetal Health Classification based on CTG using Machine learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : 26 November 2024]; 9(3) : 1177-1182. Available from: https://ijariie.com/AdminUploadPdf/Fetal_Health_Classification_based_on_CTG_using_Machine_learning_ijariie20212.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 11/26/2024 7:33:04 AM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Real-Time Hand Gesture Recognition with Finger Counting (Using OpenCV and Mediapipe)Computer scienceBhumika Sahu Download
Diffie Hellman Key Exchange Algorithm with Man in the middle attack (MITM)Computer Science EngineeringMahesh Purushottam Gajbhiye Download
AN IMPROVED ATTRIBUTE BASED ACCESS CONTROL IN PERSONAL HEALTH RECORDS USING CLOUD WITH CONSTANT CIPHERTEXT LENGTHScience and TechBitrus Isahaka Dzarma Download
Driver Drowsiness Detection System By Measuring EAR and MARComputer Engineering Zoya Fatema Khan Download
Cloud-Based File Storage and Sharing Web ApplicationComputer Science & EngineeringMohammed Aadil Download
STUDYNEST: ONLINE LEARNING PLATFORM WITH AI RECOMMENDATION SYSTEMComputer Science and Engineering Urvashi Suresh Waghmare Download
Leveraging AWS for Developing and Hosting a Dynamic Food Ordering Web ApplicationComputer EngineeringAfshin Khanam Download
Edge-to-Cloud Synergy: An Autoencoder-GAN Framework for Anomaly Detection in Healthcare Records, Financial Statements, and Secure Cloud StorageInformation TechnologyKarthik Kushala Download
E-Commerce Fraud Detection Based on Machine Learning TechniquesComputer Science EngneeringVikram Ankush Ade Download
Detection of Phishing Website Using Gradient Boosting AlgorithmComputer Science and EngineeringYAWALKAR PRASAD PRAMOD Download
Property Dealing WebComputer Science EngineeringYash Chaudhari Download
Reinforcement Learning for the Evolution of Antimicrobial Nano formulationsmachine learningMadhusudan Download
SecuraVault: A secured blockchain based cloud storage systemComputer Engineering Anshika Jaiswal Download
Autoimmune Disease Detection in women Using Machine Learning Approachcomputer science EngineeringJ. L. V. S. Download
Medicine Overdose Detection System Using Machine LearningComputer Science EngineeringDr.Somashekhar B M Download
12
For Authors
  • Submit Paper
  • Processing Charges
  • Submit Payment
Archive
  • Current Issue
  • Past Issue
IJARIIE Board
  • Member Of Board
  • Join As Board
Privacy and Policy
Follow us

Contact Info
  • +91-8401209201 (India)
  • +86-15636082010 (China)
  • ijariiejournal@gmail.com
  • M-20/234 Ami Appt,
    Nr.Naranpura Tele-Exch,
    Naranpura,
    Ahemdabad-380063
    Gujarat,India.
Copyright © 2025. IJARIIE. All Rights Reserved.