BerkKilicoglu/ML-Modelling-Disease-Analysis

Obtaining meaningful results from the data set using the model trained with machine learning methods.

27
/ 100
Experimental

This project helps healthcare professionals or researchers analyze patient health data to predict the likelihood of diabetes. By inputting anonymized health indicators like BMI, blood pressure, and lifestyle choices, it outputs a prediction of a person's diabetes status. The primary users are health data analysts or medical researchers looking to identify patterns in public health datasets.

No commits in the last 6 months.

Use this if you need to quickly build or adapt a machine learning model to predict disease risk based on a dataset of health indicators.

Not ideal if you require real-time patient diagnosis or analysis that incorporates complex, unstructured clinical notes.

public-health-analysis disease-prediction healthcare-analytics medical-research risk-assessment
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

How are scores calculated?

Stars

13

Forks

1

Language

Python

License

MIT

Last pushed

Jan 04, 2023

Commits (30d)

0

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