Machine learning for survival analysis: A survey

P Wang, Y Li, CK Reddy - ACM Computing Surveys (CSUR), 2019‏ - dl.acm.org
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 …

Mining electronic health records (EHRs) A survey

P Yadav, M Steinbach, V Kumar, G Simon - ACM Computing Surveys …, 2018‏ - dl.acm.org
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 …

Generating hypergraph-based high-order representations of whole-slide histopathological images for survival prediction

D Di, C Zou, Y Feng, H Zhou, R Ji… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
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 …

A multi-task learning formulation for survival analysis

Y Li, J Wang, J Ye, CK Reddy - Proceedings of the 22nd ACM SIGKDD …, 2016‏ - dl.acm.org
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 …

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time

H Zhao, G Cai, J Zhu, Z Dong, J Xu… - Proceedings of the 30th …, 2024‏ - dl.acm.org
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 …

The spike-and-slab lasso Cox model for survival prediction and associated genes detection

Z Tang, Y Shen, X Zhang, N Yi - Bioinformatics, 2017‏ - academic.oup.com
Motivation Large-scale molecular profiling data have offered extraordinary opportunities to
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

Y Li, L Wang, J Wang, J Ye… - 2016 IEEE 16th …, 2016‏ - ieeexplore.ieee.org
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 …

A bayesian perspective on early stage event prediction in longitudinal data

MJ Fard, P Wang, S Chawla… - IEEE Transactions on …, 2016‏ - ieeexplore.ieee.org
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 …

Mutual-assistance learning for standalone mono-modality survival analysis of human cancers

Z Ning, Z Zhao, Q Feng, W Chen… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Current survival analysis of cancers confronts two key issues. While comprehensive
perspectives provided by data from multiple modalities often promote the performance of …

Empirical comparison of continuous and discrete-time representations for survival prediction

M Sloma, F Syed, M Nemati… - Survival prediction …, 2021‏ - proceedings.mlr.press
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 …