AIMC Topic: Age Factors

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Advanced prediction of heart failure risk in elderly diabetic and hypertensive patients using nine machine learning models and novel composite indices: insights from NHANES 2003-2016.

European journal of preventive cardiology
AIMS: As the global population ages, cardiovascular diseases, particularly heart failure (HF), have become leading causes of mortality and disability among elderly patients. Diabetes and hypertension are major risk factors for cardiovascular diseases...

Moving past multidisciplinary discussions and Gender-Age-Physiology model: precision medicine through biological phenotyping in interstitial lung disease.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: Interstitial lung disease (ILD) presents significant diagnostic and therapeutic challenges due to underlying biological heterogeneity and variable clinical course. Traditional diagnostic and prognostic tools are limited in their ab...

Age and sex-specific differences of the intrafemoral and intratibial morphology using the Citak classification in patients undergoing total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Unlike established knee phenotype classifications, the recently introduced Citak classifications describe the intrafemoral and intratibial knee morphology. The aim of this study was to evaluate the distribution of Citak types A, B and C of t...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

The Journal of asthma : official journal of the Association for the Care of Asthma
PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

How to measure and model cardiovascular aging.

Cardiovascular research
Most acquired cardiovascular diseases are more common in older people, and the biological mechanisms and manifestations of aging provide insight into cardiovascular pathophysiology. Measuring aging within the cardiovascular system may help to better ...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

Nature reviews. Nephrology
The kidney is a target organ for the dysregulated host response to infection that defines sepsis, and acute kidney injury (AKI) is often an early manifestation of this response. Current sepsis criteria for adults (Sepsis-3) continue to include outmod...

Self-training EEG discrimination model with weakly supervised sample construction: An age-based perspective on ASD evaluation.

Neural networks : the official journal of the International Neural Network Society
Deep learning for Electroencephalography (EEG) has become dominant in the tasks of discrimination and evaluation of brain disorders. However, despite its significant successes, this approach has long been facing challenges due to the limited availabi...

EVALUATION OF PROGNOSTIC RISK MODELS BASED ON AGE AND COMORBIDITY IN SEPTIC PATIENTS: INSIGHTS FROM MACHINE LEARNING AND TRADITIONAL METHODS IN A LARGE-SCALE, MULTICENTER, RETROSPECTIVE STUDY.

Shock (Augusta, Ga.)
Background: Age and comorbidity significantly impact the prognosis of septic patients and inform treatment decisions. To provide clinicians with effective tools for identifying high-risk patients, this study assesses the predictive value of the age-a...