AIMC Topic: Cross-Sectional Studies

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Precision nutrition in epigenetic aging: SHAP-optimized machine learning identifies omega-3 constituent-specific associations with aging biomarkers.

Biogerontology
This cross-sectional investigation seeks to examine the association between dietary omega-3 fatty acids (including α-linolenic acid [ALA], eicosapentaenoic acid [EPA], and docosahexaenoic acid [DHA]) and biomarkers of cellular aging, specifically DNA...

An illustration of multi-class roc analysis for predicting internet addiction among university students.

PloS one
The internet is one of the essential tools today, and its impact is particularly felt among university students. Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the p...

Application of machine learning algorithms and SHAP explanations to predict fertility preference among reproductive women in Somalia.

Scientific reports
Fertility preferences significantly influence population dynamics and reproductive health outcomes, particularly in low-resource settings, such as Somalia, where high fertility rates and limited healthcare infrastructure pose significant challenges. ...

Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.

Journal of medical Internet research
BACKGROUND: Traditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting artificial intelligence (AI) model development and clinical application.

Multimodal neuroimaging unveils basal forebrain-limbic system circuit dysregulation in cognitive impairment with depression: a pathway to early diagnosis and intervention.

The journal of prevention of Alzheimer's disease
BACKGROUND: Alzheimer's disease (AD) frequently co-occurs with depressive symptoms, exacerbating both cognitive decline and clinical complexity, yet the neural substrates linking this co-occurrence remain poorly understood. We aimed to investigate th...

Knowledge and perception of artificial lntelligence education among undergraduate healthcare students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is gaining recognition for its ability to enhance patient outcomes in healthcare. Therefore, integrating AI into the undergraduate curriculum is essential to equip students with foundational knowledge before g...

Characterising corneal changes in aniridia-related keratopathy using in vivo confocal microscopy and a self-supervised AI model.

BMJ open ophthalmology
PURPOSE: To investigate whether corneal changes observed via in vivo confocal microscopy (IVCM) in patients with aniridia-related keratopathy (ARK) reflect clinical severity.

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Wearable devices are increasingly used for monitoring health and detecting digital biomarkers related to chronic diseases such as metabolic syndrome (MetS). Although circadian rhythm disturbances are known to contribute to MetS, few studi...

Medical undergraduate students' awareness and perspectives on artificial intelligence: A developing nation's context.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, yet its integration into medical education remains limited. This study assesses undergraduate healthcare students' knowledge and perceptions of AI, its applications, challenges, and th...