AIMC Topic: Proportional Hazards Models

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Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.

The Lancet. Digital health Jun 1, 2021
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...
Biomarkers, Tumor Male Middle Aged Deep Learning China Retrospective Studies Tomography, X-Ray Computed Female Progression-Free Survival Stomach Neoplasms Humans ROC Curve Disease-Free Survival Neural Networks, Computer Predictive Value of Tests Proportional Hazards Models Prognosis Area Under Curve Stomach Radiography Chemotherapy, Adjuvant
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Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs.

The Lancet. Digital health May 1, 2021
BACKGROUND: Coronary artery calcium (CAC) score is a clinically validated marker of cardiovascular disease risk. We developed and validated a novel cardiovascular risk stratification system based on deep-learning-predicted CAC from retinal photograph...
Algorithms Republic of Korea Female Aged Adult Humans Coronary Artery Disease Retina United Kingdom Proportional Hazards Models Kaplan-Meier Estimate Vascular Calcification Male Deep Learning Cardiovascular Diseases ROC Curve Middle Aged Predictive Value of Tests Risk Assessment Area Under Curve Singapore
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Computing the Hazard Ratios Associated With Explanatory Variables Using Machine Learning Models of Survival Data.

JCO clinical cancer informatics Mar 1, 2021
PURPOSE: The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models have been developed and applied to the surv...
Humans Machine Learning Algorithms Risk Factors Survival Analysis Proportional Hazards Models
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Lilikoi V2.0: a deep learning-enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.

GigaScience Jan 23, 2021
BACKGROUND: previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software.
Machine Learning Software Deep Learning Metabolomics Proportional Hazards Models
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Variable Selection for Time-to-Event Data.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
With the increasing availability of large scale biomedical and -omics data, researchers are offered with unprecedented opportunities to discover novel biomarkers for clinical outcomes. At the same time, they are also faced with great challenges to ac...
Principal Component Analysis Proportional Hazards Models Algorithms Biomarkers Genomics Regression Analysis Humans Machine Learning
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A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
Organ Dysfunction Scores Wounds and Injuries Critical Care Proportional Hazards Models Multivariate Analysis Injury Severity Score Prognosis Middle Aged Sepsis Retrospective Studies ROC Curve Critical Illness Sodium Intensive Care Units Female Hospitalization Humans Young Adult Neural Networks, Computer Adult Machine Learning Male
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Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new methodological challenges in feature selection, choosing a distance metric that captures biological...
Humans Prognosis Female Aged Aged, 80 and over Adult Leukemia, Lymphocytic, Chronic, B-Cell Male Middle Aged ZAP-70 Protein-Tyrosine Kinase Immunoglobulin Heavy Chains Unsupervised Machine Learning Mutation Proportional Hazards Models Kaplan-Meier Estimate
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Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco Jan 4, 2019
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...
Smokers Recurrence Smoking Cessation Ecological Momentary Assessment Tobacco Smoking Smartphone Machine Learning Follow-Up Studies Female Predictive Value of Tests Adult Proportional Hazards Models Male Humans Middle Aged
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Deep into Patient care: An automated deep learning approach for reshaping patient care in clinical setting.

Computer methods and programs in biomedicine Jan 1, 2019
Genome-Wide Association Study Treatment Outcome Models, Statistical Patient Care Leukocytes Programming Languages Humans Computer Simulation Medical Informatics Neural Networks, Computer Proportional Hazards Models Reproducibility of Results Software Deep Learning Algorithms Computer Systems
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Deep Integrative Analysis for Survival Prediction.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2018
Survival prediction is very important in medical treatment. However, recent leading research is challenged by two factors: 1) the datasets usually come with multi-modality; and 2) sample sizes are relatively small. To solve the above challenges, we d...
Databases, Genetic Carcinoma, Squamous Cell Proportional Hazards Models Models, Statistical Humans Brain Neoplasms Glioblastoma Neural Networks, Computer Lung Neoplasms Survival Analysis Machine Learning Computational Biology Databases, Factual
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