GlucoSense is a machine learning-based project designed to detect diabetes early using healthcare statistics and lifestyle data. It analyzes relationships between various factors to classify individuals as diabetic, pre-diabetic, or healthy.
- Data Collection and Exploration: Analyzing healthcare and lifestyle statistics to identify trends.
- Feature Selection: Using statistical and machine learning techniques to identify key attributes.
- Machine Learning Models: Implementing and evaluating various classification algorithms.
- Evaluation Metrics: Using Precision, Recall, F1 Score, and AUC to assess performance.
RahulThota-GlucoSense-Infy-Nov24/
├── data/ diabetes_data.csv
├── details/ Thumbnail.jpg
├── notebook/ GlucoSense- AI-Powered Diabetes Detection for Early Intervention.ipynb
├── requirements.txt
└── README.md
Clone the repository to your local machine:
git clone https://github.com/rahulthota21/RahulThota-GlucoSense-Infy-Nov24.gitInstall Dependencies Install the required Python packages using the provided requirements.txt file:
pip install -r requirements.txt