mahvash-siavashpour/Diabetes-Detection
The goal of this project was to detect Diabetes using XGBoost based on the information of more than 70,000 patients through the questionnaire that they filled out for the Organization for Disease Control and Prevention.
This project helps public health researchers and healthcare analysts predict whether an individual is likely to have diabetes. By inputting patient survey responses on health behaviors and demographics, it outputs a detection of diabetes. This tool would be used by public health officials, epidemiologists, or healthcare data analysts to identify at-risk populations.
No commits in the last 6 months.
Use this if you need to quickly assess diabetes risk based on patient self-reported health information and demographic data from questionnaires.
Not ideal if you need a diagnostic tool for individual patients, as this is for population-level risk assessment.
Stars
8
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Aug 01, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mahvash-siavashpour/Diabetes-Detection"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Aditya-Mankar/Diabetes-Prediction
Predict Diabetes using Machine Learning.
replicahealth/GluPredKit
GluPredKit aims to make blood glucose model training and prediction more accessible.
oladimeji-kazeem/diabetes-detection-using-ai
This repository contains code and resources for detecting diabetes using artificial intelligence...
yixiangD/AccurateBG
Patient-specific blood glucose prediction using deep learning, considering the challenges of...
Dragsters/Nutrihelp
An android application to predict risks of getting Diabetes like major health issues.