FPBoost: a gradient boosting model for survival analysis that builds hazard functions as a combination of fully parametric hazards.
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Oct 30, 2024 - Jupyter Notebook
#
scikit-survival
Here are 12 public repositories matching this topic...
Competing-risks survival re-examination of the Mayo PBC cirrhosis benchmark (UCI Cirrhosis dataset): a leakage-free, reproducible pipeline benchmarking seven models against the Mayo clinical score.
benchmark machine-learning reproducible-research biostatistics survival-analysis pbc competing-risks time-to-event liver cirrhosis scikit-survival clinical-prediction
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Jun 30, 2026 - Python
An interactive Streamlit dashboard for analyzing equipment failure patterns and predicting maintenance needs. Features include data visualization, root cause analysis using Apriori algorithm, and survival modeling with Random Survival Forests to estimate time-to-failure and optimize spare parts management.
machine-learning plotly pandas data-visualization seaborn survival-analysis matplotlib random-survival-forests association-rules apriori-algorithm predictive-maintenance streamlit scikit-survival
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Jun 23, 2025 - Jupyter Notebook
Random Survival Forest model for wildfire structure-proximity prediction · WiDS Global Datathon 2026 · Public score: 0.96373
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Jun 24, 2026 - Python
Out of sample comparison of survival models (Cox PH, RSF, Gradient Boosting) under varying censoring rates.
python data-science machine-learning simulation random-forest biostatistics survival-analysis gradient-boosting cox-proportional-hazards scikit-survival
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Jun 19, 2026 - Python
Breast cancer survival analysis using Kaplan-Meier curves, Cox proportional hazards models, and Random Survival Forests.
python data-science machine-learning survival-analysis kaplan-meier cox-model lifelines healthcare-analytics scikit-survival random-survival-forest
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May 6, 2026 - Jupyter Notebook
This project explains "prompt engineering," a key technique for guiding AI models to desired outputs in tools like chatbots and text summarizers. It highlights the importance of clear instructions and techniques like CoT Prompting for effective communication with large language models. The project also introduces the Langchain library✨.
lifelines kaplanmeierfitter prompt-tuning llm prompt-engineering chain-of-thought langchain hugging-face-api scikit-survival n-shot-prompting cot-prompting
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Feb 29, 2024 - Jupyter Notebook
Two-stage pLTV framework for mobile gaming: Cox PH + Gradient Boosting survival models predict player churn risk; LightGBM + Random Forest predict 180-day revenue. 88 tests, 27 visualisations, stakeholder-ready docs.
python data-science machine-learning lightgbm survival-analysis churn-prediction portfolio-project gaming-analytics lifetime-value scikit-survival
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Feb 26, 2026 - Jupyter Notebook
PyTorch refactor of the TCAP (Transfer-learning based Cox Proportional Hazards Network) using scikit-survival.
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Apr 23, 2026 - Python
Survival analysis for loan default timing using Cox PH and Random Survival Forest, served through FastAPI with a React dashboard
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Apr 17, 2026 - JavaScript
Reproducible pipeline for SUPPORT2 survival analysis with three-layer leakage audit, LODGO transportability benchmark, and bootstrap-validated baselines. PLOS ONE 2026.
machine-learning survival-analysis reproducibility gradient-boosting data-leakage shap support2 scikit-survival icu-mortality clinical-benchmark
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Apr 22, 2026 - Python
Interpretable machine learning framework for predicting mid-term mortality and major periprocedural complications after transcatheter aortic valve implantation (TAVI) using pre-procedural clinical, echocardiographic, CT, and cusp-specific aortic valve calcium topography data. Includes reproducible survival and classification pipelines following TRI
machine-learning scikit-learn medical-imaging survival-analysis radiology calcium computed-tomography tavi cardiology explainable-ai shap cardiovascular-medicine scikit-survival tavr aortic-valve transcatheter-aortic-valve-implantation
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Jul 10, 2026 - Python
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