Diabetes-Prediction and Diabetes-Detection

These two tools are competitors, as both aim to provide a machine learning model for diabetes prediction, differing primarily in their approach complexity and star rating.

Diabetes-Prediction
39
Emerging
Diabetes-Detection
30
Emerging
Maintenance 0/25
Adoption 9/25
Maturity 8/25
Community 22/25
Maintenance 0/25
Adoption 6/25
Maturity 9/25
Community 15/25
Stars: 112
Forks: 61
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 19
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No License Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Diabetes-Prediction

MrKhan0747/Diabetes-Prediction

Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied

This tool helps healthcare professionals and researchers predict diabetes in patients based on their health data. You input patient health metrics, and it outputs a prediction of whether the patient is likely to have diabetes. This is ideal for medical practitioners, public health analysts, and clinical researchers who need to quickly assess diabetes risk.

diabetes-risk-assessment predictive-healthcare patient-screening clinical-research public-health-analytics

About Diabetes-Detection

nileshparab42/Diabetes-Detection

A diabetes detection machine learning project involves using data and algorithms to train a model to accurately predict the likelihood of an individual having diabetes based on various features such as Glucose, age, and Blood Pressure.

Scores updated daily from GitHub, PyPI, and npm data. How scores work