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A Python package for predicting ASB risk from clinical data.

Project description

ASBPredictor

ASBPredictor is a Python package for predicting ASB (Asymptomatic Bacteriuria) risk. It uses a pre-trained RandomForestClassifier model and generates predictions based on clinical data in CSV format. This package is suitable for medical data analysis and clinical research.


Features

  • Fast Prediction: Supports batch input data and generates ASB risk predictions.
  • Easy to Use: Command-line interface for straightforward operation.
  • Flexible Input: Supports multi-row CSV input files, with results saved to a new file with predicted probabilities.
  • Customizable: Allows replacement of the default model with custom-trained models.

Installation

Install from PyPI

Run the following command:

pip install ASBPredictor

Usage

Command-Line Interface Once installed, you can run ASBPredictor directly from the command line.

Basic Command:

ASBPredictor -i <input_csv_path> -o <output_csv_path>

Example

git clone https://github.com/yangfangs/ASBPredictor.git
cd ASBPredictor/examples/
ASBPredictor -i input_data.csv -o output_data.csv

Requirements

Python version >= 3.6
Required libraries:
pandas >= 1.0.0
scikit-learn >= 1.5.0

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