There are 0 repository under kaplan-meier topic.
Survival analysis in Julia
https://www.researchgate.net/profile/Rajah_Iyer
kaplanmeier is an python library to create survival curves using kaplan-meier, and compute the log-rank test.
geneSurv: an interactive web-based tool for survival analysis in genomics research
ACM CHIL 2021: "Enabling Counterfactual Survival Analysis with Balanced Representations"
Survival modelling using Cox proportional hazard regression model
business analytics course homework assignments
Kaplan-Meier-Estimator also known as the product limit estimator.
This project focuces on analysis of survival patients with Aids, with Python library Lifelines
Survival Analysis of Lung Cancer Patients
Survival analysis functions that allow left truncation and weighting, including Aalen-Johansen, Kaplan-Meier, and Cox proportional hazards regression
Data Set on Chilean Ministers (1990-2014)
An introduction to the concepts of Survival Analysis and its implementation in lifelines package for Python.
Best practices for survival analysis at PNT Lab
Data Set on Chilean Undersecretaries (1990-2022)
:octocat: This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Prognosis" from DeepLearning.AI Coursera.
TNO MPC Lab - Protocols - Kaplan-Meier
Applying KaplanMeierFitter model on Time and Events
Minimal implementation of Kaplan-Meier and Cox proportional hazards models
This Project is a study of the patient’s survival rate due to heart failure condition caused by cardiovascular diseases. Various factors causing the disease were analyzed with the use of reliability analysis and software to model and predict patients’ survival.
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).
KM plots and Cox Proportional Hazards model for feature selection
UX Analytics & A/B Testing
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).
survival curves in ggplot2
IEEE TNNLS 2020: "Calibration and Uncertainty in Neural Time-to-Event Modeling"
ML models to predict the probability of patient survival based on various KPI's.
Examining how caffeine levels impact fly survival
tracking survival rate of new employees with a best fitted Cox Proportional Hazards model using 4 most significant personality traits
survival analysis on cirrhosis data from mayo clinic study: kaplan-meier estimator/curve, log rank test, cox proportional hazards model
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.
A survival analysis study of ovarian carcinoma patients involved in clinical trials using R