ArticleStatistics in medicine2019
Extreme learning machine Cox model for high-dimensional survival analysis.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Pre-operative prediction of BCR-free survival with mRNA variables in prostate cancer.PloS one · 2024Article
- Retrospective Analysis of Prognostic Factors in Pediatric Patients with Adrenocortical Tumor from Unique Tertiary Center with Long-Term Follow-Up.Journal of clinical medicine · 2022Review
- A scoping methodological review of simulation studies comparing statistical and machine learning approaches to risk prediction for time-to-event data.Diagnostic and prognostic research · 2022Article
- Default risk prediction and feature extraction using a penalized deep neural network.Statistics and computing · 2022Article
- Fenchel duality of Cox partial likelihood with an application in survival kernel learning.Artificial intelligence in medicine · 2021Article
- Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.JAMA network open · 2021Article
- A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.Computational and mathematical methods in medicine · 2021Article
- Application of Extreme Learning Machine in the Survival Analysis of Chronic Heart Failure Patients With High Percentage of Censored Survival Time.Frontiers in cardiovascular medicine · 2021Article
- eBreCaP: extreme learning-based model for breast cancer survival prediction.IET systems biology · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Some interesting recent studies have shown that neural network models are useful alternatives in modeling survival data when the assumptions of a classical parametric or semiparametric survival model such as the Cox (1972) model are seriously violated. However, to the best of our knowledge, the plausibility of adapting the emerging extreme learning machine (ELM) algorithm for single-hidden-layer feedforward neural networks to survival analysis has not been explored. In this paper, we present a kernel ELM Cox model regularized by an L
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.