survival-analysis

There are 23 repositories under survival-analysis topic.

lifelines
CamDavidsonPilon / lifelines
Survival analysis in Python
cox-regression data-science maximum-likelihood python reliability-analysis statistics survival-analysis
Language:Python 2321
mlr-org / mlr
Machine Learning in R
machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r survival-analysis imbalance-correction tutorial mlr learners hyperparameters-optimization feature-selection multilabel-classification clustering stacking
Language:R 1635
sebp / scikit-survival
Survival analysis built on top of scikit-learn
machine-learning python scikit-learn survival-analysis
Language:Python 1102
havakv / pycox
Survival analysis with PyTorch
deep-learning machine-learning neural-networks python pytorch survival-analysis
Language:Python 786
square / pysurvival
Open source package for Survival Analysis modeling
deep-learning machine-learning numpy python pytorch survival-analysis
Language:HTML 344
MatthewReid854 / reliability
Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/
python statistics modeling simulation data-science maximum-likelihood-estimation weibull-analysis reliability-engineering survival-analysis
Language:Python 324
loft-br / xgboost-survival-embeddings
Improving XGBoost survival analysis with embeddings and debiased estimators
survival-analysis machine-learning
Language:Python 318
autonlab / auton-survival
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
survival-analysis reliability-analysis python data-science deep-learning machine-learning time-to-event counterfactual-inference regression causal-inference graphical-models
Language:Python 312
robi56 / Survival-Analysis-using-Deep-Learning
This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
bayesian-inference cancer-research deep-learning gaussian-processes healthcare machine-learning survival-analysis time-series time-to-event
211
Miscellaneous-R-Code
m-clark / Miscellaneous-R-Code
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 **Superseded by the models-by-example repo**.
r stan jags matlab julia python bayesian mixed-models gaussian-processes factor-analysis pca em survival-analysis ordinal-regression probit irt mixture-model zip additive-models machine-learning
Language:R 194
gpstuff-dev / gpstuff
GPstuff - Gaussian process models for Bayesian analysis
bayesian gaussian-processes bayesian-inference bayesian-optimization classification regression survival-analysis spatial-analysis covariance-functions expectation-propagation variational-inference mcmc octave
Language:MATLAB 169
archd3sai / Customer-Survival-Analysis-and-Churn-Prediction
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.
customer-survival-analysis random-forest explainable-ai data-analysis flask-application survival-analysis shap-values partial-dependence-plot hazard customer-churn-prediction
Language:Jupyter Notebook 157
rk2900 / DRSA
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.
survival-analysis deep-learning machine-learning data-science
Language:Python 138
mlr3proba
mlr-org / mlr3proba
Probabilistic Learning for mlr3
density-estimation machine-learning mlr3 probabilistic-regression probabilistic-supervised-learning r r-package supervised-learning survival-analysis
Language:R 119
tylermorganwall / skpr
Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.
optimal-designs rstats design-of-experiments survival-analysis power r split-plot-designs linear-models linear-regression monte-carlo
Language:R 111
liupei101 / TFDeepSurv
COX Proportional risk model and survival analysis implemented by tensorflow.
deeplearning survival-analysis cox-regression cox-model tensorflow
Language:Python 99
autoprognosis
vanderschaarlab / autoprognosis
A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
automl survival-analysis healthcare interpretability
Language:Python 97
kokikwbt / predictive-maintenance
Datasets for Predictive Maintenance
ai-engineering industry-4 machine-learning predictive-maintenance remaining-useful-life anomaly condition-based-maintenance survival-analysis anomaly-detection time-series time-series-analysis forecasting automation phm prognosis-and-health-management run-to-failure-models run-to-failure event-to-event time-to-event degradation
Language:Jupyter Notebook 94
survex
ModelOriented / survex
Explainable Machine Learning in Survival Analysis
brier-scores cox-regression explainable-ai explainable-machine-learning explainable-ml explanatory-model-analysis interpretable-machine-learning interpretable-ml machine-learning shap survival-analysis cox-model probabilistic-machine-learning r-package censored-data time-to-event xai biostatistics variable-importance r
Language:R 94
MI2DataLab / survshap
SurvSHAP(t): Time-dependent explanations of machine learning survival models
variable-importance biostatistics brier-scores cox-model cox-regression explainable-ai probabilistic-machine-learning shap survival-analysis time-to-event explainable interpretable machine learning cph model censored survival machinelearning xai
Language:Jupyter Notebook 75
JuliaStats / Survival.jl
Survival analysis in Julia
julia statistics survival-analysis time-to-event cox-regression kaplan-meier
Language:Julia 71
huangzhii / SALMON
SALMON: Survival Analysis Learning with Multi-Omics Neural Networks
co-expression deep-learning machine-learning neural-networks survival-analysis
Language:Python 67
rk2900 / DLF
Deep learning for flexible market price modeling (landscape forecasting) in real-time bidding advertising. An implementation of our KDD 2019 paper with some other (Python) implemented prediction models.
deep-learning real-time-bidding market-price survival-analysis bid-landscape-forecasting
Language:Python 66
drizopoulos / JMbayes
Joint Models for Longitudinal and Survival Data using MCMC
joint-models longitudinal-responses survival-analysis prediction-model
Language:R 57
julianspaeth / random-survival-forest
A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.
python survival-analysis survival-prediction random-survival-forests random-forest machine-learning
Language:Python 56
nt-williams / lmtp
:package: Non-parametric Causal Effects Based on Modified Treatment Policies :crystal_ball:
causal-inference nonparametric-statistics longitudinal-data statistics machine-learning robust-statistics targeted-learning censored-data stochastic-interventions survival-analysis modified-treatment-policy precision-medicine
Language:R 55
torchsurv
Novartis / torchsurv
Deep survival analysis made easy
pytorch survival-analysis deep-learning
Language:Python 52
ActuarialIntelligence / Base
https://www.researchgate.net/profile/Rajah_Iyer
graphics-engine domain-driven-design domain-driven-designstyle interpolation annuity z-spread kaplan-meier chapman-kolmogorov black-and-scholes-pricing survival-analysis miningstructure-reader readers hadoop sql n-layer framework-actuarial-reporting fluid-reporting householderqr self-augmenting-mining-structures oracle
Language:C# 51
sdw95927 / pathology-images-analysis-using-CNN
Scripts for https://www.nature.com/articles/s41598-018-27707-4, using Convolutional Neural Network to detect lung cancer tumor area
convolutional-neural-networks pathology-image image-recognition survival-analysis
Language:Python 49
sebp / survival-cnn-estimator
Tutorial on survival analysis using TensorFlow.
tensorflow survival-analysis deep-learning time-to-event convolutional-neural-networks tutorial notebook
Language:Jupyter Notebook 48
derrynknife / SurPyval
A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.
survival-analysis parametric-methods probability-plot parametric-distribution weibull reliability reliability-engineering churn-prediction non-parametric risk-analysis actuarial-science reliability-analysis
Language:Python 47
pammtools
adibender / pammtools
Piece-wise exponential Additive Mixed Modeling tools
additive-models pamm pammtools piece-wise-exponential r rstats survival-analysis
Language:R 46
arturomoncadatorres / deepsurvk
Implementation of DeepSurv using Keras
survival-analysis data-science deep-learning keras tensorflow2
Language:Python 43
RyanWangZf / SurvTRACE
SurvTRACE: Transformers for Survival Analysis with Competing Events
survival-analysis time-to-event
Language:Python 43
soda-inria / hazardous
Competing Risks and Survival Analysis
competing-risks data-science gradient-boosting machine-learning survival-analysis
Language:Python 43
giabaio / survHE
Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.
frequentist hamiltonian-monte-carlo health-economic-evaluation inla plotting-survival-curves rstan survival-analysis survival-models uncertainty
Language:R 41