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Machine learning for survival analysis: A survey
Survival analysis is a subfield of statistics where the goal is to analyze and model data
where the outcome is the time until an event of interest occurs. One of the main challenges …
where the outcome is the time until an event of interest occurs. One of the main challenges …
Mining electronic health records (EHRs) A survey
The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
Generating hypergraph-based high-order representations of whole-slide histopathological images for survival prediction
Patient survival prediction based on gigapixel whole-slide histopathological images (WSIs)
has become increasingly prevalent in recent years. A key challenge of this task is achieving …
has become increasingly prevalent in recent years. A key challenge of this task is achieving …
A multi-task learning formulation for survival analysis
Predicting the occurrence of a particular event of interest at future time points is the primary
goal of survival analysis. The presence of incomplete observations due to time limitations or …
goal of survival analysis. The presence of incomplete observations due to time limitations or …
Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time
In video recommendation, an ongoing effort is to satisfy users' personalized information
needs by leveraging their logged watch time. However, watch time prediction suffers from …
needs by leveraging their logged watch time. However, watch time prediction suffers from …
The spike-and-slab lasso Cox model for survival prediction and associated genes detection
Motivation Large-scale molecular profiling data have offered extraordinary opportunities to
improve survival prediction of cancers and other diseases and to detect disease associated …
improve survival prediction of cancers and other diseases and to detect disease associated …
Transfer learning for survival analysis via efficient l2, 1-norm regularized cox regression
In survival analysis, the primary goal is to monitor several entities and model the occurrence
of a particular event of interest. In such applications, it is quite often the case that the event of …
of a particular event of interest. In such applications, it is quite often the case that the event of …
A bayesian perspective on early stage event prediction in longitudinal data
Predicting event occurrence at the early stage of a longitudinal study is an important and
challenging problem which has high practical value in many real-world applications. As …
challenging problem which has high practical value in many real-world applications. As …
Mutual-assistance learning for standalone mono-modality survival analysis of human cancers
Current survival analysis of cancers confronts two key issues. While comprehensive
perspectives provided by data from multiple modalities often promote the performance of …
perspectives provided by data from multiple modalities often promote the performance of …
Empirical comparison of continuous and discrete-time representations for survival prediction
Survival prediction aims to predict the time of occurrence of a particular event of interest,
such as the time until a patient dies. The main challenge in survival prediction is the …
such as the time until a patient dies. The main challenge in survival prediction is the …