AIMC Topic: Aged

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Machine learning models of depression in middle-aged and older adults with cardiovascular metabolic diseases.

Journal of affective disorders
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) is increasing, and depression in CMD patients significantly impacts prognosis. Therefore, this study aimed to develop and validate a predictive model for depression in CMD patients ...

Functional connectome-based predictive modeling of suicidal ideation.

Journal of affective disorders
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...

Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.

Heart (British Cardiac Society)
BACKGROUND: Coronary artery disease (CAD) is linked to an increased risk of mild cognitive impairment (MCI). Effective and convenient screening methods for identifying MCI from the CAD population are still lacking. This study aims to develop a deep l...

Identification of key factors and explainability analysis for surgical decision-making in hepatic alveolar echinococcosis assisted by machine learning.

World journal of gastroenterology
BACKGROUND: Echinococcosis, caused by Echinococcus parasites, includes alveolar echinococcosis (AE), the most lethal form, primarily affecting the liver with a 90% mortality rate without prompt treatment. While radical surgery combined with antiparas...

External validation of an AI-based preoperative frailty index using real-world data.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Preoperative frailty assessment is crucial for surgical risk stratification in older adults. Traditional frailty measurements are often too time-consuming and resource-intensive in preoperative settings. This study aimed to externally val...

History matters: Preventing severe allergic transfusion reactions.

American journal of clinical pathology
OBJECTIVE: Prior studies have shown that pretransfusion medication is not effective in preventing allergic transfusion reactions (ATRs), but these studies did not consider the patient's history of ATR. This study evaluated whether pretransfusion anti...

Machine Learning Algorithms for Predicting Urinary Tract Infections: Integration of Demographic Data and Dipstick Reflectance Results.

Clinical chemistry
BACKGROUND: Urinary tract infections (UTIs) are among the most common infections encountered in healthcare settings. Current diagnostic practices often require 24-48 h due to the time needed for culture results. Given that 70%-80% of cultures return ...

At-home wearables and machine learning capture motor impairment and progression in adult ataxias.

Brain : a journal of neurology
A significant barrier to developing disease-modifying therapies for spinocerebellar ataxias (SCAs) and multiple system atrophy of the cerebellar type (MSA-C) is the scarcity of tools to measure disease progression sensitively in clinical trials. Wear...

Prognostication in patients with idiopathic pulmonary fibrosis using quantitative airway analysis from HRCT: a retrospective study.

The European respiratory journal
BACKGROUND: Predicting shorter life expectancy is crucial for prioritising antifibrotic therapy in fibrotic lung diseases (FLDs), where progression varies widely, from stability to rapid deterioration. This heterogeneity complicates treatment decisio...