AIMC Topic: Middle Aged

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Developing a Two-Dimensional Size-Exclusion Liquid Chromatography Platform for Isolating the High-Quality Extracellular Vesicles to Predict and Evaluate Metabolic Improvement Outcomes of Sleeve Gastrectomy.

Analytical chemistry
The direct analysis of plasma exosomal components still presents significant challenges due to the interference of high concentrations of albumin, immunoglobulins, and other abundant proteins. Herein, we developed a two-dimensional size-exclusion liq...

A robust automated segmentation method for white matter hyperintensity of vascular-origin.

NeuroImage
White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmenta...

Development and validation of a machine learning model based on complete blood counts to predict clinical outcomes in urothelial carcinoma patients.

Clinica chimica acta; international journal of clinical chemistry
Urothelial carcinoma (UC) is a highly malignant disease with significant public health implications. Despite advancements in oncology, early diagnosis and effective prognostic tools remain limited. This study aimed to develop a machine learning model...

A Transformer-Based Framework for Counterfactual Estimation of Antihypertensive Treatment Effect on COVID-19 Infection Risk - A Proof-of-Concept Study.

American journal of hypertension
BACKGROUND: Transformer-based neural networks excel in modelling high-dimensional, time-series data with complex dependencies. This proof-of-concept study applies a transformer-X-learner framework to estimate treatment effects using real-world data, ...

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...

Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.

Journal of affective disorders
BACKGROUND: Clinical studies have shown that facial expressions and body posture in depressed patients differ significantly from those of healthy individuals. Combining relevant behavioral features with artificial intelligence technology can effectiv...

Metabolomic machine learning predictor for arsenic-associated hypertension risk in male workers.

Journal of pharmaceutical and biomedical analysis
Arsenic (As)-induced hypertension is a significant public health concern, highlighting the need for early risk prediction. This study aimed to develop a predictive model for occupational As exposure and hypertension using metabolomics and machine lea...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Prospective quality control in chest radiography based on the reconstructed 3D human body.

Physics in medicine and biology
Chest radiography requires effective quality control (QC) to reduce high retake rates. However, existing QC measures are all retrospective and implemented after exposure, often necessitating retakes when image quality fails to meet standards and ther...