AIMC Topic: Adult

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Assist me or replace me? Uncovering the influence of AI awareness on employees' counterproductive work behaviors.

Frontiers in public health
OBJECTIVE: Drawing on the conservation of resources theory (COR), the research aims to reveal the influence of artificial intelligence (AI) awareness on employees' mental health and behaviors, particularly examining whether and how employees' AI awar...

Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.

Annals of Saudi medicine
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...

Machine learning based classification of excessive smartphone users via neuronal cue reactivity.

Psychiatry research. Neuroimaging
Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data an...

A machine learning algorithm for the identification elevated Lp(a) in patients with, or high-risk of having, coronary heart disease.

International journal of cardiology
BACKGROUND: Decision tree algorithms, obtained by machine learning, provide clusters of patients with similar clinical patterns by the identification of variables that best merge with a given dependent variable.

People's judgments of humans and robots in a classic moral dilemma.

Cognition
How do ordinary people evaluate robots that make morally significant decisions? Previous work has found both equal and different evaluations, and different ones in either direction. In 13 studies (N = 7670), we asked people to evaluate humans and rob...

Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence.

Journal of hazardous materials
Chronic exposure to arsenic is linked to the development of cancers in the skin, lungs, and bladder. Arsenic exposure manifests as variegated pigmentation and characteristic pitted keratosis on the hands and feet, which often precede the onset of int...

Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

Anaesthesia, critical care & pain medicine
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...

Accelerated 2D radial Look-Locker T1 mapping using a deep learning-based rapid inversion recovery sampling technique.

NMR in biomedicine
Efficient abdominal coverage with T1-mapping methods currently available in the clinic is limited by the breath hold period (BHP) and the time needed for T1 recovery. This work develops a T1-mapping framework for efficient abdominal coverage based on...

Automated orofacial virtual patient creation: A proof of concept.

Journal of dentistry
OBJECTIVES: To (1) construct a virtual patient (VP) using facial scan, intraoral scan, and low-dose computed tomography scab based on an Artificial intelligence (AI)-approach, (2) quantitatively compare it with AI-refined and semi-automatic registrat...