Metadata-Version: 2.1
Name: mipha
Version: 0.1.0
Summary: Modular data Integration for Predictive Healthcare Analytics
Author-email: Hadrien Salem <hadrien.salem@centralelille.fr>
Maintainer-email: Hadrien Salem <hadrien.salem@centralelille.fr>
License: MIT License
        
        Copyright (c) 2024 Hadrien Salem
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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        SOFTWARE.
        
Project-URL: Homepage, https://github.com/SnowHawkeye/mipha
Project-URL: Bug Reports, https://github.com/SnowHawkeye/mipha/issues
Project-URL: Source, https://github.com/SnowHawkeye/mipha
Keywords: machine learning,data science,healthcare,disease prediction
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Provides-Extra: dev
Requires-Dist: check-manifest; extra == "dev"
Provides-Extra: test
Requires-Dist: coverage; extra == "test"

# MIPHA

**Modular data Integration for Predictive Healthcare Analytics**

MIPHA is a framework allowing for the creation of reusable, transferable and highly-customizable machine learning models
for disease prediction. Its key features are:

- Flexible architecture allowing for the study of any disease
- Ability to include data from various sources
- Modular architecture designed for reusability

This framework is being worked on as part of my PhD research on disease prediction using machine learning.
Development is still in its early stages! Documentation of the library will be updated over time.

## Release summary

### [0.1.0] Initial prototype - 2024-07-25

#### Summary

This very first development allows for the instantiation of a disease prediction model, and will be built upon in subsequent iterations.

#### Added

- Initialize project
- Implement the core components of the framework
- Allow for saving, loading and reusing components of the framework
- Introduce unit tests and test utilities
- Set up continuous integration tools

#### Changed

#### Fixed
