| _version_ | 1866901594524614656 |
|---|---|
| author | Indrajit swain |
| author_facet | Indrajit swain |
| contents | <h3>Overview</h3> <p>This release contains a production-ready implementation of a multimodal machine learning framework for cancer risk prediction using The Cancer Genome Atlas (TCGA) data and XGBoost models. This code accompanies PhD research on multimodal cancer risk assessment.</p> <h2>Repository Contents</h2> <ul> <li><strong>Data preprocessing pipeline</strong>: Comprehensive preprocessing for TCGA multimodal datasets (<code>TGCA_data_preprocessing.ipynb</code>)</li> <li><strong>XGBoost model implementation</strong>: Production-ready cancer risk classification model</li> <li><strong>Documentation</strong>: Complete usage instructions and methodology overview</li> </ul> <h2>Features</h2> <ul> <li>Multimodal data integration (genomic, clinical, and other TCGA data types)</li> <li>Robust XGBoost-based risk prediction framework</li> <li>Reproducible preprocessing and analysis pipeline</li> <li>Ready for academic research and citation</li> </ul> <h2>Academic Use</h2> <p>This code is suitable for direct use in research projects and can be cited using the DOI generated by Zenodo. The implementation is stable and has been validated for PhD research purposes.</p> <h2>Citation</h2> <p>Please cite this work using the DOI badge provided by Zenodo after publication of this release.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18093157 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | indrajeetapache/tcga-multimodal-xgb-cancer-risk: v1.0.0 - TCGA Multimodal XGBoost Cancer Risk Prediction Model Indrajit swain <h3>Overview</h3> <p>This release contains a production-ready implementation of a multimodal machine learning framework for cancer risk prediction using The Cancer Genome Atlas (TCGA) data and XGBoost models. This code accompanies PhD research on multimodal cancer risk assessment.</p> <h2>Repository Contents</h2> <ul> <li><strong>Data preprocessing pipeline</strong>: Comprehensive preprocessing for TCGA multimodal datasets (<code>TGCA_data_preprocessing.ipynb</code>)</li> <li><strong>XGBoost model implementation</strong>: Production-ready cancer risk classification model</li> <li><strong>Documentation</strong>: Complete usage instructions and methodology overview</li> </ul> <h2>Features</h2> <ul> <li>Multimodal data integration (genomic, clinical, and other TCGA data types)</li> <li>Robust XGBoost-based risk prediction framework</li> <li>Reproducible preprocessing and analysis pipeline</li> <li>Ready for academic research and citation</li> </ul> <h2>Academic Use</h2> <p>This code is suitable for direct use in research projects and can be cited using the DOI generated by Zenodo. The implementation is stable and has been validated for PhD research purposes.</p> <h2>Citation</h2> <p>Please cite this work using the DOI badge provided by Zenodo after publication of this release.</p> |
| title | indrajeetapache/tcga-multimodal-xgb-cancer-risk: v1.0.0 - TCGA Multimodal XGBoost Cancer Risk Prediction Model |
| url | https://doi.org/10.5281/zenodo.18093157 |