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Peterlanhao/A-Machine-Learning-Approach-to-Diagnose-Chromosomal-Copy-Number-Variations: v0.22

Authors: Peterlanhao;

Peterlanhao/A-Machine-Learning-Approach-to-Diagnose-Chromosomal-Copy-Number-Variations: v0.22

Abstract

v0.22 - Zenodo publish Changes Zenodo publish v0.21 - PCA update Changes Optimizing the code for interpretable models v0.2 - Code Documentation & README Enhancement Changes Added English module-level docstrings to all Python scripts (.py) Added descriptive Markdown cells to Jupyter notebooks (.ipynb) Renamed "Model Weights" section to "Data and Model Availability" in both READMEs, clarifying that training/test data and pre-trained model weights are available from the corresponding author upon reasonable request v0.11 - Readme Update Changes Added Chinese version of README (README_CN.md) Updated project documentation Initial Release This is the first official release of the ensemble machine learning framework for diagnosing chromosomal copy number variations (CNVs) in hematological malignancies.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average