Genomic-Classification-of-Acute-Lymphoblastic-Leukemia-Using-AI-Towards-Personalized-Medicine: First stable release
Description
Release Notes: Initial public release of the code and models used for the study: Genomic Classification of Acute Lymphoblastic Leukemia Using AI: Towards Personalized Medicine. Includes data preprocessing, feature extraction, model training scripts (CNN, LSTM, Dense), and ensemble meta-learner implementation.
Release Description: This release provides the complete codebase supporting the study on AI-driven genomic classification of acute lymphoblastic leukemia subtypes. All scripts are fully documented to allow reproducibility of results, including data preprocessing, feature selection, deep learning model training, meta-learner integration, and evaluation metrics calculation. The release is intended for researchers and practitioners in computational biology, bioinformatics, and medical AI.
Files
Genomic-Classification-of-Acute-Lymphoblastic-Leukemia-Using-AI-Towards-Personalized-Medicine-main.zip
Files
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Additional details
Related works
- Is described by
- Journal article: 10.1101/2025.09.20.25336225 (DOI)
- Is supplement to
- Software: https://github.com/AlirezaRahi/Genomic-Classification-of-Acute-Lymphoblastic-Leukemia-Using-AI-Towards-Personalized-Medicine/tree/v.1.000 (URL)
Software
- Repository URL
- https://github.com/AlirezaRahi/Genomic-Classification-of-Acute-Lymphoblastic-Leukemia-Using-AI-Towards-Personalized-Medicine
- Programming language
- Python