AIMC Topic: Proportional Hazards Models
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Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems.
JCO clinical cancer informatics
Jan 1, 2023
PURPOSE: We developed a deep neural network that queries the lung computed tomography-derived feature space to identify radiation sensitivity parameters that can predict treatment failures and hence guide the individualization of radiotherapy dose. I...
VdistCox: Vertically distributed Cox proportional hazards model with hyperparameter optimization.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2023
Vertically partitioned data is distributed data in which information about a patient is distributed across multiple sites. In this study, we propose a novel algorithm (referred to as VdistCox) for the Cox proportional hazards model (Cox model), which...
SurvBenchmark: comprehensive benchmarking study of survival analysis methods using both omics data and clinical data.
GigaScience
Jul 30, 2022
Survival analysis is a branch of statistics that deals with both the tracking of time and the survival status simultaneously as the dependent response. Current comparisons of survival model performance mostly center on clinical data with classic stat...
Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.
International journal of epidemiology
Jun 13, 2022
BACKGROUND: Machine learning-based risk prediction models may outperform traditional statistical models in large datasets with many variables, by identifying both novel predictors and the complex interactions between them. This study compared deep le...
Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk.
Age and ageing
Apr 1, 2022
BACKGROUND: ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture ageing-related physiological changes compared with chronological age (CA).
Stratified neural networks in a time-to-event setting.
Briefings in bioinformatics
Jan 17, 2022
Deep neural networks are frequently employed to predict survival conditional on omics-type biomarkers, e.g., by employing the partial likelihood of Cox proportional hazards model as loss function. Due to the generally limited number of observations i...
Electrocardiography-Based Artificial Intelligence Algorithm Aids in Prediction of Long-term Mortality After Cardiac Surgery.
Mayo Clinic proceedings
Dec 1, 2021
OBJECTIVE: To assess whether an electrocardiography-based artificial intelligence (AI) algorithm developed to detect severe ventricular dysfunction (left ventricular ejection fraction [LVEF] of 35% or below) independently predicts long-term mortality...
An artificial neural network model based on DNA damage response genes to predict outcomes of lower-grade glioma patients.
Briefings in bioinformatics
Nov 5, 2021
Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However,...
Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression.
Briefings in bioinformatics
Sep 2, 2021
Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM cells release glutamate and show an abnormality, but differ in cellular behavior. So, t...
Humans
Central Nervous System
Gene Regulatory Networks
Molecular Sequence Annotation
Proportional Hazards Models
Computational Biology
Gene Ontology
Kaplan-Meier Estimate
Gene Expression Regulation, Neoplastic
Neoplasm Proteins
Atlases as Topic
Signal Transduction
Glioblastoma
Glutamic Acid
Machine Learning
Datasets as Topic
Brain Neoplasms
Gene Expression Profiling
Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patien...
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