AIMC Topic: Survival Analysis
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deepAFT: A nonlinear accelerated failure time model with artificial neural network.
Statistics in medicine
Jun 18, 2024
The Cox regression model or accelerated failure time regression models are often used for describing the relationship between survival outcomes and potential explanatory variables. These models assume the studied covariates are connected to the survi...
Survival trend and outcome prediction for pediatric Hodgkin and non-Hodgkin lymphomas based on machine learning.
Clinical and experimental medicine
Jun 18, 2024
Pediatric Hodgkin and non-Hodgkin lymphomas differ from adult cases in biology and management, yet there is a lack of survival analysis tailored to pediatric lymphoma. We analyzed lymphoma data from 1975 to 2018, comparing survival trends between 7,8...
Deep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan.
European stroke journal
Jun 16, 2024
BACKGROUND: Predicting functional impairment after intracerebral hemorrhage (ICH) provides valuable information for planning of patient care and rehabilitation strategies. Current prognostic tools are limited in making long term predictions and requi...
Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia.
Computers in biology and medicine
Jun 13, 2024
BACKGROUND: Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and the fifth most common malignancy in children, necessitating advanced technologies for outcome prediction.
Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate.
Artificial intelligence in medicine
May 23, 2024
We present a neural network framework for learning a survival model to predict a time-to-event outcome while simultaneously learning a topic model that reveals feature relationships. In particular, we model each subject as a distribution over "topics...
Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.
Scientific reports
May 13, 2024
Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These ...
Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network.
BMC medical informatics and decision making
May 7, 2024
In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit...
Deep Survival Analysis With Latent Clustering and Contrastive Learning.
IEEE journal of biomedical and health informatics
May 6, 2024
Survival analysis is employed to analyze the time before the event of interest occurs, which is broadly applied in many fields. The existence of censored data with incomplete supervision information about survival outcomes is one key challenge in sur...
Survival estimation of oral cancer using fuzzy deep learning.
BMC oral health
May 2, 2024
BACKGROUND: Oral cancer is a deadly disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop a fuzzy deep learning (FDL)-based model to estimate the survival time based on clinicopathologic data of oral...
ECG-surv: A deep learning-based model to predict time to 1-year mortality from 12-lead electrocardiogram.
Biomedical journal
May 1, 2024
BACKGROUND: Electrocardiogram (ECG) abnormalities have demonstrated potential as prognostic indicators of patient survival. However, the traditional statistical approach is constrained by structured data input, limiting its ability to fully leverage ...
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