Survival analysis in Julia
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Updated
Jun 22, 2026 - Julia
Survival analysis in Julia
kaplanmeier is an python library to create survival curves using kaplan-meier, and compute the log-rank test.
Modern survival analysis for Python.
geneSurv: an interactive web-based tool for survival analysis in genomics research
ACM CHIL 2021: "Enabling Counterfactual Survival Analysis with Balanced Representations"
Clinical oncology statistical analytics platform for survival analysis, patient cohort stratification, and Kaplan-Meier estimation.
Survival analysis functions that allow left truncation and weighting, including Aalen-Johansen, Kaplan-Meier, and Cox proportional hazards regression
Survival Analysis of Lung Cancer Patients
Survival modelling using Cox proportional hazard regression model
Data Set on Chilean Ministers (1990-2014)
business analytics course homework assignments
survival curves in ggplot2
Cox modeling and censoring-aware survival validation with IPCW metrics
Kaplan-Meier-Estimator also known as the product limit estimator.
IEEE TNNLS 2020: "Calibration and Uncertainty in Neural Time-to-Event Modeling"
Best practices for survival analysis at PNT Lab
This project focuces on analysis of survival patients with Aids, with Python library Lifelines
KM plots and Cox Proportional Hazards model for feature selection
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