AIMC Topic: Machine Learning

Clear Filters Showing 27741 to 27750 of 34417 articles

Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic pulmonary angiography.

International journal of cardiology
BACKGROUND: Pulmonary hypertension (pH) is a malignant pulmonary circulation disease. Right heart catheterization (RHC) is the gold standard procedure for quantitative evaluation of pulmonary hemodynamics. Accurate and noninvasive quantitative evalua...

Characterization of volatile flavour compounds and characteristic flavour precursors in poultry eggs based on multi-omics and machine learning.

Food chemistry
Although egg flavour influences consumer preference and satisfaction, the features governing the flavour profiles have been poorly studied. This study investigated the volatile compounds and lipid profiles of different poultry egg yolks (chicken, duc...

The risk factors for relapse behavior in individuals with substance use disorders: An interpretable machine learning study.

Journal of affective disorders
BACKGROUND: Substance abuse has become a serious public health problem worldwide, and finding effective prevention and treatment strategies is undoubtedly an urgent need. This study addresses the risk factors that lead to relapse behaviors among subs...

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 ...

A scientometric analysis of machine learning in schizophrenia neuroimaging: Trends and insights (2012-2024).

Journal of affective disorders
Machine learning applications in schizophrenia neuroimaging research have undergone significant evolution since 2012. However, a comprehensive scientometric analysis of this field has not yet been conducted. This study analyzed 315 original research ...

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...

Non-destructive assessment of tissue engineered cartilage maturity using visible and near infrared spectroscopy combined with machine learning.

Biosensors & bioelectronics
Tissue engineering is a promising approach to address the unmet clinical need for treating cartilage damage. Monitoring the characteristics of tissue-engineered cartilage constructs (TECs) during culture is critical for optimizing culture conditions ...

Machine Learning and Artificial Intelligence for Research on Hypertension.

American journal of hypertension
Hypertension continues to be the leading modifiable risk factor for mortality globally, contributing significantly to cardiovascular disease. The American Heart Association (AHA) 2017 Hypertension Guidelines define hypertension as blood pressure (BP)...

ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction.

Journal of chemical information and modeling
Atomic charge is a fundamental quantum chemical property essential for advancing drug design and discovery. Although quantum mechanics (QM) methods offer the highest level of accuracy, their computational demands scale quadratically with the number o...