AIMC Topic: Proportional Hazards Models

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Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting.

Journal of evaluation in clinical practice Dec 12, 2017
RATIONALE, AIMS AND OBJECTIVES: A common approach to assessing treatment effects in nonrandomized studies with time-to-event outcomes is to estimate propensity scores and compute weights using logistic regression, test for covariate balance, and then...
Male Middle Aged Comorbidity Time Factors Socioeconomic Factors Humans Machine Learning Female Pulmonary Disease, Chronic Obstructive Sex Factors Patient Readmission Survival Analysis Proportional Hazards Models Propensity Score Monte Carlo Method Age Factors Models, Statistical Decision Trees Health Services Heart Failure
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Bladder contractility index in posterior urethral valve: A new marker for early prediction of progression to renal failure.

Journal of pediatric urology Nov 22, 2017
INTRODUCTION: Posterior urethral valve (PUV) is the most common cause of pediatric end stage renal disease (ESRD), imposing a major health burden on medical community caregivers and adversely affecting the quality of life of patients. Chronic kidney ...
Urinary Bladder Urinary Bladder Neck Obstruction Urodynamics Vesico-Ureteral Reflux Child, Preschool Child Male Follow-Up Studies ROC Curve Humans Risk Assessment Predictive Value of Tests India Databases, Factual Disease Progression Kidney Failure, Chronic Biomarkers Renal Insufficiency, Chronic Cohort Studies Retrospective Studies Proportional Hazards Models Time Factors Female Muscle Contraction Urethral Stricture
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A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

Scientific reports Oct 12, 2017
Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignor...
Survival Analysis Proportional Hazards Models Humans Algorithms Neoplasms Supervised Machine Learning
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Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 5, 2017
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...
Proportional Hazards Models Reproducibility of Results Liver Neoplasms Biomarkers, Tumor Gene Regulatory Networks Gene Expression Profiling Genomics Humans Transcriptome Computational Biology Deep Learning Algorithms Proteomics Prognosis Metabolomics
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A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

Scientific reports Aug 21, 2017
Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, ...
Machine Learning Kidney Transplantation Clinical Decision-Making Female Reproducibility of Results Humans Graft Survival Follow-Up Studies Models, Statistical Decision Trees Area Under Curve Transplant Recipients Adult Male Middle Aged Comorbidity Cohort Studies Proportional Hazards Models
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Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice Jul 3, 2017
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...
Cholesterol Sex Factors Survival Analysis Proportional Hazards Models Machine Learning Computer Simulation Aged Adult Cardiovascular Diseases Middle Aged Time Factors Body Mass Index Age Factors Decision Trees Blood Pressure Humans
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DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique.

NMR in biomedicine May 25, 2017
This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimat...
Models, Neurological Glioblastoma Survival Analysis Proportional Hazards Models Adolescent Time Factors Contrast Media Magnetic Resonance Imaging Humans Aged, 80 and over Fuzzy Logic Female Young Adult Aged Adult Brain Neoplasms Male Middle Aged
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Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents.

Chinese journal of cancer Feb 27, 2017
BACKGROUND: Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast cancer patients a...
Taiwan Proportional Hazards Models Humans Neural Networks, Computer Female Breast Neoplasms Logistic Models
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Learning Effective Treatment Pathways for Type-2 Diabetes from a clinical data warehouse.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Treatment guidelines for management of type-2 diabetes mellitus (T2DM) are controversial because existing evidence from randomized clinical trials do not address many important clinical questions. Data from Electronic Medical Records (EMRs) has been ...
Machine Learning Electronic Health Records Female Metformin Male Humans Aged Proportional Hazards Models Middle Aged Adult Critical Pathways Diabetes Mellitus, Type 2 Consolidation Chemotherapy Hypoglycemic Agents Sitagliptin Phosphate Glycated Hemoglobin
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Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: Prognostic value.

Journal of cardiovascular computed tomography Dec 28, 2016
BACKGROUND: There is no published data on the prognostic value of global myocardial perfusion values at stress dynamic CT myocardial perfusion imaging (CTMPI).
United States Europe Predictive Value of Tests Coronary Angiography Registries Coronary Artery Disease Myocardial Infarction Proportional Hazards Models Kaplan-Meier Estimate Asia Myocardial Revascularization Aged Male Middle Aged Risk Assessment Severity of Illness Index Computed Tomography Angiography Prognosis Humans Coronary Circulation Retrospective Studies Myocardial Perfusion Imaging Female Angina, Unstable Risk Factors Coronary Stenosis Hospitalization
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