> For the complete documentation index, see [llms.txt](https://www.mlcompendium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.mlcompendium.com/business-domains/survival-analysis.md).
# Survival Analysis
1. **A good** [**introduction**](http://www.stat.columbia.edu/~madigan/W2025/notes/survival.pdf) **for Survival Analysis,** [**Intro**](https://medium.com/analytics-vidhya/survival-analysis-an-introduction-87a94c98061)**,** [**brief intro**](https://medium.com/geekculture/survival-analysis-a-brief-introduction-e814f88a7a42)**,** [**Intuition**](https://towardsdatascience.com/survival-analysis-intuition-implementation-in-python-504fde4fcf8e)
2. [**what is?** ](https://medium.com/inside-machine-learning/survival-analysis-cb5832ffcd78)
3. [**survival scikit kit**](https://scikit-survival.readthedocs.io/en/stable/user_guide/00-introduction.html#What-is-Survival-Analysis?)
4. Survival Analysis: Leveraging Deep Learning for Time-to-Event Forecasting Part [I](https://towardsdatascience.com/survival-analysis-predict-time-to-event-with-machine-learning-part-i-ba52f9ab9a46) & [II](https://towardsdatascience.com/survival-analysis-predict-time-to-event-with-machine-learning-part-i-ba52f9ab9a46)\
5. [Deep Learning for Survival Analysis Authors: Laura Löschmann, Daria Smorodina](https://humboldt-wi.github.io/blog/research/information_systems_1920/group2_survivalanalysis/)
6. [(Paper) A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction](https://www.nature.com/articles/s41598-020-77220-w#Sec7)
7. [This repository](https://github.com/czifan/DeepSurv.pytorch) is an unofficial pytorch implementation of [DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network](https://link.springer.com/article/10.1186/s12874-018-0482-1). We reimplement the experiments in the paper, which is followed by [Github](https://github.com/jaredleekatzman/DeepSurv), and the detailed understanding is available on my [Blog](https://www.cnblogs.com/CZiFan/p/12674144.html).
8. [DeepSurv Keras](https://github.com/arturomoncadatorres/deepsurvk)
9. [DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks](https://github.com/chl8856/DeepHit)
10. [Comparing DeepHit and DeepSurv models on the SUPPORT dataset](https://github.com/ryancburke/DNN_survival/tree/main)
11. [Survival analysis with PyTorch](https://github.com/havakv/pycox)
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