AIMC Topic: Proportional Hazards Models
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Feature-weighted survival learning machine for COPD failure prediction.
Artificial intelligence in medicine
Mar 28, 2019
Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting su...
Risk Factors
Hospitalization
Aged
Aged, 80 and over
Pulmonary Disease, Chronic Obstructive
Prognosis
Retrospective Studies
Electronic Health Records
Female
Canada
Age Factors
Predictive Value of Tests
Sex Factors
Patient Readmission
Male
Middle Aged
Severity of Illness Index
Time Factors
ROC Curve
Humans
Machine Learning
Biomarkers
Survival Analysis
Proportional Hazards Models
Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.
Scientific reports
Mar 26, 2019
Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine lea...
Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods.
Journal of gynecologic oncology
Mar 11, 2019
OBJECTIVES: The aim of this study was to develop a new prognostic classification for epithelial ovarian cancer (EOC) patients using gradient boosting (GB) and to compare the accuracy of the prognostic model with the conventional statistical method.
Using machine learning and an ensemble of methods to predict kidney transplant survival.
PloS one
Jan 9, 2019
We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. The proposed model achieved better performance, measured by Harrell's concordance index, than the Esti...
Machine learning models to predict disease progression among veterans with hepatitis C virus.
PloS one
Jan 4, 2019
BACKGROUND: Machine learning (ML) algorithms provide effective ways to build prediction models using longitudinal information given their capacity to incorporate numerous predictor variables without compromising the accuracy of the risk prediction. C...
The Role of GDF-15 in Heart Failure Patients With Chronic Kidney Disease.
The Canadian journal of cardiology
Dec 26, 2018
BACKGROUND: Growth differentiation factor-15 (GDF-15) is a stress-inducible cytokine and member of the transforming growth factor-β cytokine superfamily that refines prognostic assessment in subgroups of patients with heart failure (HF). We evaluated...
Heart Transplantation
Cholesterol
Proportional Hazards Models
Middle Aged
Sodium
Systole
Renal Insufficiency, Chronic
Sex Factors
Natriuretic Peptide, Brain
Humans
Glomerular Filtration Rate
Heart-Assist Devices
Angiotensin Receptor Antagonists
Biomarkers
Follow-Up Studies
Angiotensin-Converting Enzyme Inhibitors
Female
Blood Pressure
Growth Differentiation Factor 15
Male
Heart Failure, Systolic
Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.
American journal of obstetrics and gynecology
Dec 21, 2018
BACKGROUND: Historically, the Cox proportional hazard regression model has been the mainstay for survival analyses in oncologic research. The Cox proportional hazard regression model generally is used based on an assumption of linear association. How...
Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.
Journal of biomedical informatics
Oct 30, 2018
BACKGROUND: One of the significant problems in the field of healthcare is the low survival rate of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest can provide the time required for intervening and preventing its ...
Experience With Hypothermic Machine Perfusion in Expanded Criteria Donors: Functional Outcomes.
Transplantation proceedings
Sep 18, 2018
UNLABELLED: Hypothermic machine perfusion (HMP) decreases delayed graft function (DGF) and improves 1-year graft survival in expanded criteria donors (ECDs). Time of HMP could be associated with incidence of DGF.
Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.
The Lancet. Respiratory medicine
Sep 16, 2018
BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumoni...
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