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@lshpaner lshpaner released this 04 May 20:35
· 34 commits to main since this release

What's New in kfre 0.1.5

This stable release, kfre 0.1.5, builds directly upon the foundations set in version 0.1.2 and 0.1.4 with no changes to the codebase. The key highlight of this update is a an update of citing version 0.1.5 under citations section on PyPI landing page.

Version 0.1.4: Documentation Enhancements

Core Documentation Migration: All essential documentation has been transferred to a new site, available at lshpaner.github.io/kfre_docs. This migration enhances accessibility and ease of navigation.

Visual Updates: A new logo has been introduced, now featured on both the documentation site and the PyPI landing page to enhance brand recognition.

Citation Instructions: Detailed guidance on how to properly cite the kfre project has been added, including a direct link to the Zenodo archive for easy reference.

Updated References: All references have been meticulously updated to conform with the latest APA 7 standards.

Why No Version 0.1.3?
In alignment with common superstitions, version 0.1.3 was skipped, much like how many buildings lack a 13th floor.

Version 0.1.2. marked a substantial update from the preliminary alpha versions, introducing significant enhancements and features that elevate the tool’s flexibility, accuracy, and ease of use:

Enhanced Core Functionality: A comprehensive overhaul from earlier minimal viable products to a more robust and feature-rich application.

New Calculator Function: The introduction of the kfre_person() function enables risk metrics calculations for individuals one at a time, customizing the analysis to each unique dataset.

Increased Flexibility: The add_kfre_risk_col() function now allows for direct execution of kfre without the need to instantiate a class, simplifying the process for users.

Model Variability: Users can specify models with 4, 6, or 8 variables through the add_kfre_risk_col() function, adapting to different data requirements.

Timeframe Options: The function now accommodates specification of projection years (2 or 5 years, or either), providing tailored risk assessments.

DataFrame Handling: An option to either copy the dataframe or modify it in place when adding kfre columns is now available, offering greater flexibility in data management.

Formula Correction: The formula for the 6-variable calculation has been updated with the correct coefficients from Tangri et al., enhancing prediction accuracy.

Conversion Tools: The perform_conversions() function facilitates the conversion of relevant clinical metrics, streamlining data preparation for analysis.

This release reflects ongoing efforts to enhance and refine kfre, driven by feedback from users and continuous research into improving its utility and functionality.

Full Changelog: https://lshpaner.github.io/kfre_docs/changelog