AIMC Topic: Adolescent

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YOLO11m-cls applied to sex and age classification based on the radiographic analysis of the nasal aperture.

Scientific reports
Deep learning tools based on computer vision have emerged as alternative methods for assessing radiographic image patterns. These approaches have been explored for various forensic applications, including sex and age estimation. This study aimed to e...

Level-1-visual perspective taking for human and robot avatars.

Psychological research
Research on level 1 visual perspective taking (L1-VPT) has been debating whether L1-VPT is an implicit socially rooted or rather a non-social process. Using online versions of the Dot Perspective Task by Samson et al. (Journal of Experimental Psychol...

Uncovering age-specific subtypes of pediatric obesity and metabolic syndrome using machine learning algorithms.

Scientific reports
Identifying new subgroups among children and adolescents with obesity and metabolic syndrome requires advanced clustering techniques capable of analyzing complex multidimensional data. This study aimed to employ machine learning methods to enhance th...

Unveiling the burden of snakebite injuries: an EQ-5D-5 L-based evaluation of health-related quality of life.

BMC public health
BACKGROUND: Snakebite envenoming remains poorly understood in terms of long-term health-related quality of life (HRQoL), particularly in China where standardized assessments are lacking. This study is the first to comprehensively evaluate HRQoL impai...

Impact of contrast enhancement boost and super-resolution deep learning reconstruction on pediatric congenital heart disease CTA scans: ultra-low contrast dose.

BMC medical imaging
OBJECTIVE: To evaluate the feasibility of using contrast enhancement boost (CE-Boost) combined with super-resolution deep learning reconstruction (SR-DLR) to reduce contrast agent dosage in pediatric patients with congenital heart disease (CHD).

MRI multi-sequence deep learning integration with clinical profiles for pediatric viral encephalitis diagnosis.

Scientific reports
Pediatric viral encephalitis is an acute central nervous system infection caused by various viruses, with diverse clinical manifestations and challenges in early diagnosis. The traditional diagnostic methods lack sufficient sensitivity and specificit...

Explainable machine-learning-based predictions of blood lead levels and school drinking water contamination among children: a case study in Washington DC.

Scientific reports
Water quality degradation poses significant risks to human health, ecosystem, and community. Many cities continue to rely on outdated pipes and water distribution networks that are highly susceptible to leaks, corrosion, and lead contamination. The p...

Optimizing machine learning models for predicting health service access and determinants among pregnant women in rural Ethiopia.

Scientific reports
Pregnant women in rural Ethiopia face substantial barriers to accessing adequate healthcare services, contributing to adverse maternal and neonatal health outcomes. Traditional statistical approaches often fall short in capturing the complex, nonline...

Acceptance of healthcare services based on the large language model in China: a national cross-sectional study.

BMC public health
BACKGROUND: Increasing public acceptance of medical large language models will be beneficial for further leveraging their potential in reducing medical costs and improving efficiency. The objective of our research is to figure out the acceptance of h...

AI chatbots as 'pocket doctors': intimate health support for young women in Lebanon.

BMC public health
BACKGROUND: In conservative societies such as Lebanon and the broader Middle East and North Africa region, gynecological and intimate health issues are heavily stigmatized, limiting young women's access to care due to fear of judgment, privacy concer...