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
MAYANK GUPTA
, PRINCE KARAVADIYA , SAKSHI GORE , SHUBHAM UBALE , PROF. KANCHAN DHOMSE
Unique Id:
IJSDR2303019
Published In:
Volume 8 Issue 3, March-2023
Abstract:
Recently diabetes is a disease caused by a group of metabolic disorders. It is also known as Diabetic mellitus. It affects the human body organs. Diabetes can be controlled by predicting this disease earlier. If diabetics patient is untreated for a long time, it may lead to high level of blood sugar. Now a days, healthcare industries generating large volume of data. Different Machine Learning algorithms and statistics are used to predict the disease with the help of past and current data. Machine learning techniques helps the doctors to predict diabetes at early stage. Patient’s medical record and different types of algorithms are added in dataset for experimental analysis. we use logistic regression, random forest, decision tree classifier and gradient boosting to predict whether a patient based on diagnostic measurements has diabetes or not. So, in applied algorithm performance and accuracy is compared and discussed in the project.
Keywords:
CNN, FCM, Medical Image, segmentation, SVM
Cite Article:
"DIABETES PREDICTION USING MACHINE LEARNING", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.91 - 94, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303019.pdf
Downloads:
000337070
Publication Details:
Published Paper ID: IJSDR2303019
Registration ID:204367
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 91 - 94
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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