AIMC Topic: Middle Aged

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Qualitative and quantitative assessment of accelerated liver diffusion-weighted imaging using deep-learning reconstruction in oncologic patients.

BMC medical imaging
BACKGROUND: Deep-learning (DL) reconstructions could improve image quality and reduce acquisition time in diffusion-weighted imaging (DWI). This study assessed, qualitatively and quantitatively, DL-DWI in liver metastasis of colorectal cancer patient...

LightMG-Net: an efficient lightweight deep neural network for multiclass grading of retinal detachment using handcrafted statistical mechanisms.

Scientific reports
Retinal detachment is a severely curable eye condition that becomes a genuine factor for the increased visual acuity worldwide. If neglected, it may result significant visual impairment in individuals aged 60 to 69 years. The successful cure percenta...

The global epidemiology, risk factors, and mortality prediction of nocardiosis: an easily missed opportunistic infection.

Scientific reports
This study was to comprehensively investigate the epidemiology of nocardiosis worldwide and develop an interpretable machine learning (ML) model to predict mortality in patients with nocardiosis. The PubMed and Web of Science databases were searched ...

Comparison of Machine Learning Models for Colon Cancer Survival: Predictive Modeling Approach.

JMIR cancer
BACKGROUND: Colon cancer is a leading cause of cancer-related deaths worldwide, with survival influenced by risk factors, treatment type, and patient characteristics. Traditional statistical models, such as Kaplan-Meier curves, have been widely used ...

TLMACEA: design of a transfer learning model for correlative analysis of auscultation and clinical parameters via explainable AI-based recommender.

Biomedical physics & engineering express
Auscultations are commonly used to analyze lung conditions through signal processing and classification techniques. However, the efficiency of these models is often limited by factors like signal quality, sensor performance, and dataset size. Current...

Machine learning meets maternal health: Uncovering spatial blind spots in antenatal care quality in Bangladesh.

PloS one
BACKGROUND: High-quality antenatal care (ANC) is defined as four or more antenatal visits with at least one to a medically trained provider, measurement of weight and blood pressure, testing of blood and urine, and receipt of information on potential...

Predicting arthritis risk with machine learning: Insights from the 2023 National Health Interview Survey data.

PloS one
Arthritis, a common chronic disease encompassing multiple subtypes of osteoarthritis and rheumatoid arthritis, was explored in this study as a risk-related factor based on data from the 2023 U.S. National Health Interview Survey (NHIS). The study inc...

Mechanism of triptolide in the treatment of gastric cancer with diabetes through JAK2/STAT3 pathway.

European journal of pharmacology
Univariate and multivariate Cox analyses revealed a correlation between diabetes and the prognosis of gastric cancer patients (p < 0.05). Using bioinformatics, Serine/threonine-protein kinase pim-1 (PIM1) was identified as the core target gene of tri...

Multi-omics analysis reveal clinical-gut-brain interactions in female ibs patients with adverse childhood experiences.

Biology of sex differences
BACKGROUND: The brain-gut system, which involves bidirectional communication between the central nervous system and the gut, plays a central role in stress responses. Its dysregulation is implicated in irritable bowel syndrome (IBS), a stress-sensiti...

Income, psychological security, and subjective well-being in urban China: a machine learning analysis with SHAP interpretation.

BMC psychology
BACKGROUND: Subjective well-being has become a core indicator for measuring social progress and policy effectiveness. However, the "Easterlin Paradox" remains prevalent, and this paradox refers to the disconnect between economic growth and improvemen...