AIMC Topic: Young Adult

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Artificial Intelligence-based Assessment of Facial Symmetry Aesthetics of Saudi Arabian Population.

Facial plastic surgery : FPS
The purpose of this study is to investigate facial symmetry aesthetics (FSA) in the Saudi Arabian population using artificial intelligence (AI).Two hundred and ten people from a range of demographic backgrounds participated in an observational cross-...

Development and external validation of a machine learning model to predict diabetic nephropathy in T1DM patients in the real-world.

Acta diabetologica
AIMS: Studies on machine learning (ML) for the prediction of diabetic nephropathy (DN) in type 1 diabetes mellitus (T1DM) patients are rare. This study focused on the development and external validation of an explainable ML model to predict the risk ...

Impact of upper extremity robotic rehabilitation on respiratory parameters, functional capacity and dyspnea in patients with stroke: a randomized controlled study.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Stroke leads to reduced mobility and functional capacity, also negatively affects respiratory functions and muscle strength.

Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.

Applied psychology. Health and well-being
Social-emotional skills are vital for individual development, yet research on which skills most effectively promote students' mental and physical health, particularly from a global perspective, remains limited. This study aims to address this gap by ...

Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.

Journal of epidemiology and global health
BACKGROUND: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This st...

Deep-learning models reveal how context and listener attention shape electrophysiological correlates of speech-to-language transformation.

PLoS computational biology
To transform continuous speech into words, the human brain must resolve variability across utterances in intonation, speech rate, volume, accents and so on. A promising approach to explaining this process has been to model electroencephalogram (EEG) ...

Large language models can outperform humans in social situational judgments.

Scientific reports
Large language models (LLM) have been a catalyst for the public interest in artificial intelligence (AI). These technologies perform some knowledge-based tasks better and faster than human beings. However, whether AIs can correctly assess social situ...

Developmental changes in the perceived moral standing of robots.

Cognition
Emerging evidence suggests that children may think of robots-and artificial intelligence, more generally-as having moral standing. In this paper, we trace the developmental trajectory of this belief. Over three developmental studies (combined N = 415...

Height prediction of individuals with osteogenesis imperfecta by machine learning.

Orphanet journal of rare diseases
BACKGROUND: Osteogenesis imperfecta (OI) is a genetic disorder characterized by low bone mass, bone fragility and short stature. There is a significant gap in knowledge regarding the growth patterns across different types of OI, and the prediction of...

Predictive modeling of gestational weight gain: a machine learning multiclass classification study.

BMC pregnancy and childbirth
BACKGROUND: Gestational weight gain (GWG) is a critical factor influencing maternal and fetal health. Excessive or insufficient GWG can lead to various complications, including gestational diabetes, hypertension, cesarean delivery, low birth weight, ...