INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
EFFICIENT FETAL HEALTH PREDICTION USING DATA SCIENCE
Authors Name:
L. Murali Nadh
, G. Srimanth , k. Pavan Kumar Goud , G. Nagakoteswarao , Mrs. T. Usha
Unique Id:
IJSDR2304274
Published In:
Volume 8 Issue 4, April-2023
Abstract:
The growth of technology in our day-to-day enterprise with advanced machines are outstanding through involving data science all over the world.Fetal monitoring during pregnancy time is the most important to save the life of the mother as well as the child. In this project, we present a data science technique that is used to measure the fetal heart rate during the time of pregnancy. The major component used for this detection is Fetal Digital stethoscope sensor which is to be placed on the abdomen of the pregnant and the signals are processed by the micro-controller used and the accurate fetal heart rate. This system is very flexible and low cost helps the patient to monitor the fetal heart rate in home. We will use data science method for our project .In our project house rent is predicted by algorithms namely Decision Tree (DT) and Recurrent Neural Network (RNN) in terms of accuracy. From our work we can prove that our proposed works better than other existing algorithms.
Keywords:
Fetal Health, Neural Network, CNN Model.
Cite Article:
"EFFICIENT FETAL HEALTH PREDICTION USING DATA SCIENCE", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1752 - 1756, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304274.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR2304274
Registration ID:205596
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1752 - 1756
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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