Explainable Machine Learning in Survival Analysis

:package: Non-parametric Causal Effects Based on Modified Treatment Policies :crystal_ball:

ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification

deploy your own new www tor*.onion in 10 seconds using 1 file only

:package: R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

Imputation of zeros, nondetects and missing data in compositional data sets

Reproduction of the work by Hong, Y., Meeker, W. Q., & McCalley, J. D. (2009). Prediction of remaining life of power transformers based on left truncated and right censored lifetime data. Annals of Applied Statistics, 3(2), 857-879.

Simple Mixed Effect Models and Censoring

Enhance content integrity using CustomCensorify: a JavaScript module. Efficiently replace sensitive words for respectful communication. Code and example included.

COMPASS: an open-source, general-purpose software toolkit for computational psychiatry

FPBoost: a gradient boosting model for survival analysis that builds hazard functions as a combination of fully parametric hazards.

Kendall's Tau for Two-Sample Inference Problems

The "rcens" package provides functions to generate censored samples of type I, II and III, from any random sample generator. It also provides the option to create left and right censorship. Along with this, the generation of samples with interval censoring is in the testing phase. With two options of fixed length intervals and random lengths.

Random or Extremely Random Forest for censored quantile regression.

:octocat: This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Prognosis" from DeepLearning.AI Coursera.

Notebooks supporting my PyData Global 2024 talk

tcensReg is a package written to obtain maximum likelihood estimates from a truncated normal distribution with censoring.

Predicting the inhibitory response of drugs using Graph Convolutional Networks trained on censored data.

The work had been done with Prof. Biswabrata Pradhan, Indian Statistical Institute, Kolkata. A tree-based method for censored survival data is discussed, based on maximizing the difference in survival between groups of patients by the Log-Rank statistic value based criterion.

R package for `Dynamic Regression with Recurrent Events'

R library for creating means of censored data

:speech_balloon: Talk on causal inference and variable importance with stochastic interventions under two-phase sampling

[Archived] Master's project (SIUE, 2023): MLE for series system reliability with Weibull components under right-censoring and masked failure data. See likelihood.model.series.md for active software.

Masked-cause likelihood models for series systems with arbitrary hazard components in R

Este repositório apresenta um projeto de Inteligência Comercial e Marketing com Python e PowerBI, com um dashboard desenvolvido para analisar o desempenho de vendas em 2024.

Course materials for a university course including lecture slides and assignments focused on survival analysis techniques. Assignments involve data preparation, statistical modeling with Julia, and report generation using LaTeX, covering topics like Kaplan-Meier estimation, , Weibull distributions, and censoring.

Sparse Graphical Models with Censored or Missing Data

make your web censored 🤭

A complete pipeline to train and test DeepHit time to event prediction model using synthetic data including right censored data with competing risk.

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