DIABETES PREDICTION USING MACHINE LEARNING
MAYANK GUPTA
, PRINCE KARAVADIYA , SAKSHI GORE , SHUBHAM UBALE , PROF. KANCHAN DHOMSE
CNN, FCM, Medical Image, segmentation, SVM
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.
"DIABETES PREDICTION USING MACHINE LEARNING", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.91 - 94, March-2023, Available :https://ijsdr.org/papers/IJSDR2303019.pdf
Volume 8
Issue 3,
March-2023
Pages : 91 - 94
Paper Reg. ID: IJSDR_204367
Published Paper Id: IJSDR2303019
Downloads: 000347232
Research Area: Engineering
Country: -, -, -
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
