Survival analysis in Python
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Updated
Jun 26, 2024 - Python
Survival analysis in Python
Machine Learning in R
Survival analysis built on top of scikit-learn
Survival analysis with PyTorch
Open source package for Survival Analysis modeling
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/
This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.
GPstuff - Gaussian process models for Bayesian analysis
Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper and a benchmark for several (Python) implemented survival analysis methods.
Improving XGBoost survival analysis with embeddings and debiased estimators
Scripts for https://www.nature.com/articles/s41598-018-27707-4, using Convolutional Neural Network to detect lung cancer tumor area
Foundations of Strategic Business Analytics - ESSEC Business school via Coursera.org
COX Proportional risk model and survival analysis implemented by tensorflow.
A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
Joint Models for Longitudinal and Survival Data using MCMC
Datasets for Predictive Maintenance
Survival analysis in Julia
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