AIMC Topic: Humans

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Automated Multitier Tagging of Chinese Online Health Education Resources Using a Large Language Model: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Precision health promotion, which aims to tailor health messages to individual needs, is hampered by the lack of structured metadata in vast digital health resource libraries. This bottleneck prevents scalable, personalized content delive...

Real-world evaluation of the accuracy of the Viz.AI automated intracranial hemorrhage volume calculation tool.

Journal of neurointerventional surgery
BACKGROUND: Appropriate management of spontaneous intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) requires rapid, accurate volume estimation. Viz.AI has developed an artificial intelligence (AI)-powered ICH calculation tool that ...

Age-dependent effects of surgical approach in T3b differentiated thyroid carcinoma: a population-based analysis using machine learning.

Endocrine-related cancer
Current guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC) with gross strap muscle invasion, yet evidence supporting this universal approach remains limited and conflicting. We analyzed 6,920 T3b DTC patients ...

An evaluation of Roluperidone as a promising repurposing candidate for Alzheimer's Disease: A Computational Investigation.

PloS one
Alzheimer's disease (AD) is the most dominant and prevalent form of dementia. The therapeutic agents for AD are not sufficient. Drug repurposing (i.e., also called drug repositioning or therapeutic switching of drugs) could contribute to adding novel...

Estimating weaning duration from incremental dentine δ15N and δ13C using a sequence-based LSTM neural network: A deep learning framework for bioarchaeological applications.

PloS one
The estimation of weaning duration from incremental dentine δ15N and δ13C values offers insights into health, nutrition, and demography in past populations. In this study, we developed a novel machine learning approach to estimate weaning duration us...

Identifying daily-living features related to loneliness: A causal machine learning approach.

PloS one
BACKGROUND: Loneliness is a distressing feeling that influences well-being. Immigrants' experience of acculturation to a new dominant culture places them at risk for maladaptive behaviors and daily rhythms leading to loneliness. Identifying daily-liv...

Key personality and training factors influencing athletes' mental health - based on machine learning.

PloS one
Athletes face a higher risk of mental health disorders compared to the general population, and prior theoretical and empirical work suggests that personality traits and training-related factors may play important roles in shaping athletes' mental hea...

Biological age threshold is associated with symptomatic knee osteoarthritis risk in chinese adults: Insights from machine learning analysis of a national cohort.

PloS one
BACKGROUND: Symptomatic knee osteoarthritis (KOA) imposes a substantial global health and economic burden. Although chronological age (CA) is a key risk factor, it poorly reflects interindividual aging heterogeneity. Biological age (BA), which is qua...

Surface proteome of plasma extracellular vesicles differentiates between SARS-CoV-2 and influenza infection.

Virulence
Small extracellular vesicles (sEVs) play a role in the pathophysiology of viral respiratory infections and may be suitable biomarkers for COVID-19 and Influenza infections, or targets for treatment. We investigated differences in the surface proteome...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Previous studies have reported comorbidity between MS and psoriasis, but the underlying mechanisms remain unclear. This study aims to elucidate the shar...