Time-to-Event Prediction

12 papers with code • 0 benchmarks • 2 datasets

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Datasets


Most implemented papers

Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks

autonlab/DeepSurvivalMachines 2 Mar 2020

We describe a new approach to estimating relative risks in time-to-event prediction problems with censored data in a fully parametric manner.

Interpretable machine learning for time-to-event prediction in medicine and healthcare

modeloriented/survex 17 Mar 2023

Time-to-event prediction, e. g. cancer survival analysis or hospital length of stay, is a highly prominent machine learning task in medical and healthcare applications.

Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning

Cogito2012/CarCrashDataset 1 Aug 2020

The derived uncertainty-based ranking loss is found to significantly boost model performance by improving the quality of relational features.

auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data

autonlab/auton-survival 15 Apr 2022

Applications of machine learning in healthcare often require working with time-to-event prediction tasks including prognostication of an adverse event, re-hospitalization or death.

Time-to-Event Prediction with Neural Networks and Cox Regression

havakv/pycox 1 Jul 2019

New methods for time-to-event prediction are proposed by extending the Cox proportional hazards model with neural networks.

Variational Learning of Individual Survival Distributions

ZidiXiu/VSI 9 Mar 2020

The abundance of modern health data provides many opportunities for the use of machine learning techniques to build better statistical models to improve clinical decision making.

A Deep Variational Approach to Clustering Survival Data

i6092467/vadesc ICLR 2022

In this work, we study the problem of clustering survival data $-$ a challenging and so far under-explored task.

Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models

ZhiliangWu/DKAFT 26 Jul 2021

Recurrent neural network based solutions are increasingly being used in the analysis of longitudinal Electronic Health Record data.

SurvSHAP(t): Time-dependent explanations of machine learning survival models

mi2datalab/survshap 23 Aug 2022

Experiments on synthetic and medical data confirm that SurvSHAP(t) can detect variables with a time-dependent effect, and its aggregation is a better determinant of the importance of variables for a prediction than SurvLIME.

A copula-based boosting model for time-to-event prediction with dependent censoring

alimid/clayton_boost 10 Oct 2022

A characteristic feature of time-to-event data analysis is possible censoring of the event time.