AIMC Topic: Humans

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Machine learning algorithms to predict khat chewing practice and its predictors among men aged 15 to 59 in Ethiopia: further analysis of the 2011 and 2016 Ethiopian Demographic and Health Survey.

Frontiers in public health
INTRODUCTION: Khat chewing is a significant public health issue in Ethiopia, influenced by various demographic factors. Understanding the prevalence and determinants of khat chewing practices is essential to developing targeted interventions. Therefo...

Future horizons in diabetes: integrating AI and personalized care.

Frontiers in endocrinology
Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditional markers like HbA1c are insufficient for capturing short-term glycemic fluctuations, leading to the need for more precise metrics such as Glucose Var...

Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.

Frontiers in endocrinology
PURPOSE: We aimed to identify the mitochondria-related feature genes associated with type 2 diabetes mellitus and explore their potential roles in immune cell infiltration.

Attribute encryption access control method of high dimensional medical data based on fuzzy algorithm.

PloS one
The current approach to data access control predominantly utilizes blockchain technology. However, when dealing with high-dimensional medical data, the inherent transparency of blockchain conflicts with the necessity of protecting patient privacy. Co...

Enhancing treatment adherence in dialysis patients through digital health interventions: a systematic review and meta-analysis of randomized controlled trials.

Renal failure
OBJECTIVE: To systematically assess the efficacy of digital health interventions (DHIs) for improving treatment adherence among dialysis patients through a meta-analysis of randomized controlled trials (RCTs).

Early warning of deep coal miners' unsafe behavior based on the HFACS-CM-BP neural network.

International journal of occupational safety and ergonomics : JOSE
Preventing miners' unsafe behavior and reducing accidents in deep coal mines are crucial. This study comprehensively used methods such as the human factor analysis and classification system for China mines (HFACS-CM) model, grounded theory and the ba...

Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample.

European journal of psychotraumatology
Digital technologies offer tremendous potential to predict dysregulated mood and behavior within an individual's environment, and in doing so can support the development of new digital health interventions. However, no prediction models have been bu...

Monocyte distribution width (MDW) as a reliable diagnostic biomarker for sepsis in patients with HIV.

Emerging microbes & infections
Sepsis is a leading cause of death among patients with HIV, but early diagnosis remains a challenge. This study evaluates the diagnostic performance of monocyte distribution width (MDW) in detecting sepsis in patients with HIV. A prospective observat...

Evaluating potential for AI automation of quantitative and semi-quantitative MRI scoring in arthritis, especially at the knee: a systematic literature review.

Skeletal radiology
OBJECTIVE: This systematic review explores key quantitative and semi-quantitative MRI-based scoring systems for arthritis biomarkers, focusing on their potential for automation through AI.

Health shocks and health behavior: a long-term perspective.

The European journal of health economics : HEPAC : health economics in prevention and care
Several empirical papers suggest that individuals improve health-related behaviors in response to adverse shocks to physical health. However, little evidence exists regarding the questions of (i) how long-lasting these behavioral responses are and (i...