AIMC Topic: Proportional Hazards Models

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Association between hemoglobin glycation index and 28-day all-cause mortality in acute myocardial infarction patients: Analysis of the MIMIC-IV database.

PloS one
Acute myocardial infarction (AMI) substantially fuels the worldwide escalation in both morbidity and mortality. The hemoglobin glycation index (HGI) is linked to a range of undesirable outcomes, but its relationship with short-term outcomes in AMI pa...

Cox proportional hazards model with Bayesian neural network for survival prediction.

Scientific reports
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...

Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data.

Scientific reports
Glioblastoma is an aggressive, malignant primary brain tumour and the most prevalent histological type of glioma. Our study attempted to investigate the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in Asian patie...

Unsupervised clustering of biochemical markers reveals health profiles associated with function and survival in active aging.

Scientific reports
This study explores the relationships between biochemical phenotypes identified using machine learning, and key health outcomes, including body composition, physical function, and mortality risk. Data were collected from 536 physically active Spanish...

Multi-modal machine learning classifier for idiopathic pulmonary fibrosis predicts mortality in interstitial lung diseases.

Respiratory investigation
BACKGROUND: Interstitial lung disease (ILD) prognostication incorporates clinical history, pulmonary function testing (PFTs), and chest CT pattern classifications. The machine learning classifier, Fibresolve, includes a model to help detect CT patter...

Association between albumin-corrected anion gap and delirium in acute pancreatitis: insights from the MIMIC-IV database.

BMC gastroenterology
BACKGROUND: Delirium frequently occurs as a severe complication among patients with acute pancreatitis (AP), contributing to extended hospital stays, higher mortality rates, and lasting cognitive deficits. The pathogenesis of delirium in this setting...

Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.

Scientific reports
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...

Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.

Nature communications
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...