ML models to predict the probability of patient survival based on various KPI's.
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Feb 1, 2022 - R
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kaplan-meier
Here are 72 public repositories matching this topic...
A machine learning project focused on predicting chronic kidney disease (CKD) stages and performing survival analysis using clinical biomarkers. It utilizes the Kaplan-Meier estimator to analyze patient progression and visualize survival probabilities, offering insights into CKD management.
python machine-learning scikit-learn data-visualization statistical-analysis survival-analysis data-preprocessing feature-engineering predictive-modeling kaplan-meier chronic-kidney-disease healthcare-data clinical-data-analysis
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Jan 11, 2025 - Jupyter Notebook
Simple library to help calculate and graph survival curves.
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Mar 12, 2018 - Ruby
Applying KaplanMeierFitter model on Time and Events
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Feb 7, 2021 - Jupyter Notebook
Determined how long a patient is likely to survive advanced inoperable lung cancer when treated with chemotherapy (standard treatment) vs chemotherapy combined with a new drug (test treatment).
regression healthcare statistical-analysis survival-analysis kaplan-meier parametric-modelling semi-parametric-modeling
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Nov 12, 2020 - R
🚙 Comprehensive driver risk analytics using Cox proportional hazards (C-index: 0.79) and Bayesian hierarchical models (91.4% accuracy) ⚡ Production-ready system with real-time scoring for 300K+ drivers, SHAP explainability, and full Docker/Kubernetes deployment stack
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Sep 28, 2025 - Python
Frequency Table, Chi-Squared & ANOVA Test, KM Model, Median Time Comparison, Log-Rank & Wilcoxon Test, Tukey Multiple Comparison, Immortal Time Bias, Cox Model, Proportional Hazards Assumption Tests, Supremum Test for Functional Form. *NCDB data is publicly available. Team members: Kah Meng Soh, Dr. Lynette Smith, Dr. Sharma Smriti, Dr. Apar Ganti.
kaplan-meier cox-regression log-rank-test chisquare-test wilcoxon-test anova-test multiplecomparison smallcelllungcancer
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Jan 31, 2025 - SAS
Coursework, Stata code, and notes for PBHS 32700: Biostatistical Methods (Spring 2024, University of Chicago). Topics include contingency tables, logistic regression, Poisson and negative binomial models, and survival analysis using Kaplan-Meier, Cox, and parametric models. The course emphasizes categorical and time-to-event analysis using Stata.
survival-analysis logistic-regression hazard-ratios kaplan-meier cox-regression ordinal-regression contingency-table poisson-regression nomial-data cox-proportional-hazard
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Jul 16, 2025 - Stata
UX Analytics & A/B Testing
bigquery correlation clustering pca survival-analysis logistic-regression ab-testing mca kmeans glm kaplan-meier anova cox-model kmeans-clustering ab-test generalized-linear-models log-rank-test chi2-contingency chi2
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Sep 7, 2021 - Python
Analyzed employee turnover (Jan 2022 - Mar 2023) at my former organization, considering trends, departmental attrition, and tenure insights. Used predictive analytics from the 2022 Employee Engagement Survey to identify groups with flight risk. Incorporated Survival Analysis for temporal patterns, guiding decisions to improve retention.
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Aug 11, 2024 - Python
Multi-agent AI system for evidence-based oncology clinical decision support with physician oversight – Kaggle AI Agents Capstone 2025
python pubmed kaggle healthcare gemini kaplan-meier oncology ai-agents clinical-decision-support multi-agent-system medical-ai streamlit llm agent-orchestration
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Nov 29, 2025 - Python
This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Prognosis" from DeepLearning.AI Coursera.
numpy hazard pandas imputation linear-model missing-data survival kaplan-meier decision-tree time-to-event risk-model heart-disease overfitting mortality-rates censored-data prognosis c-index concordance-index
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Jan 1, 2023 - Jupyter Notebook
A preprocessor to construct medical history table from data source
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Jun 22, 2021 - R
Survival Analysis on the patients from a trial of laser coagulation for the treatment of diabetic retinopathy. Survival times in this dataset are actual time to blindness in months, minus the minimum possible time to event (6.5 months).
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Jul 27, 2022 - R
End-to-end workflow on synthetic accelerated life test (ALT) data: dataset generation, Kaplan–Meier survival analysis, Weibull-2P modeling, and Arrhenius temperature acceleration. Includes Py scripts, Jupyter notebooks, plots, and CSV outputs.
reliability-engineering survival-analysis kaplan-meier semiconductor reliability-analysis data-science-projects failure-analysis weibull-analysis arrhenius-model
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Aug 16, 2025 - Jupyter Notebook
Small-sample bias of the Kaplan-Meier Estimator
jupyter-notebook survival-analysis maple kaplan-meier bias maxima maxima-cas efron-estimator survival-curve product-limit-estimator small-sample-bias gill-estimator lifetime-curve
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Sep 1, 2025 - Jupyter Notebook
business analytics course homework assignments
ggplot2 r random-forest eda feature-selection bayesian-network survival-analysis logistic-regression kaplan-meier cox-regression decision-tree churn-prediction lime ctree churn-modeling
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Apr 6, 2020 - HTML
A survival analysis study of ovarian carcinoma patients involved in clinical trials using R
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Apr 9, 2024
Create the covariate-adjusted Kaplan-Meier and cumulative incidence functions
statistics survival-analysis confidence-intervals kaplan-meier sampling-methods cumulative-incidence covariate-adjustment
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Mar 8, 2023 - JavaScript
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