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Predicting Suicidal Ideation Among Youths With Autism Spectrum Disorder: An Advanced Machine Learning Study.

Clinical psychology & psychotherapy
This study aimed to predict suicidal ideation among youth with autism spectrum disorder (ASD) by applying machine learning techniques. A cross-sectional sample of 368 ASD-diagnosed young people (aged 18-24 years) was recruited, and 34 candidate predi...

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning.

PloS one
Meningococcal meningitis poses a significant public health burden in the meningitis belt region of sub-Saharan Africa. The introduction of the meningococcal PsA-TT vaccine (MenAfriVac®) has successfully eliminated Neisseria meningitidis serogroup A (...

Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

PloS one
Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present...

Waist rotation angle as indicator of probable human collision-avoidance direction for autonomous mobile robots.

PloS one
The likelihood of pedestrians encountering autonomous mobile robots (AMRs) in smart cities is steadily increasing. While previous studies have explored human-to-human collision avoidance, the behavior of humans avoiding AMRs in direct, head-on scenar...

Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators.

PloS one
OBJECTIVES: Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan government has been collecting clinical indica...

Multidimensional correlates of psychological stress: Insights from traditional statistical approaches and machine learning using a nationally representative Canadian sample.

PloS one
Approximately one-fifth of Canadians report high levels of psychological stress. This is alarming, as chronic stress is associated with non-communicable diseases and premature mortality. In order to create effective interventions and public policy fo...

How Successful Is AI in Developing Postsurgical Wound Care Education Material?

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
ChatGPT can be used as an aid in education, research and clinical management. This study was conducted using the ChatGPT 4.0 program to develop artificial intelligence-supported wound care education material that can be read and understood by patient...

All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.

Clinical interventions in aging
INTRODUCTION: The aim of this study was to identify the influencing factors for all-cause mortality in elderly patients with intertrochanteric and femoral neck fractures and to construct predictive models.

Deep learning-based fine-grained assessment of aneurysm wall characteristics using 4D-CT angiography.

PeerJ
PURPOSE: This study proposes a novel deep learning-based approach for aneurysm wall characteristics, including thin-walled (TW) and hyperplastic-remodeling (HR) regions.

Psychometric assessment of the Persian translated version of the "medical artificial intlligence readiness scale for medical students".

PloS one
BACKGROUND: Artificial intelligence (AI) has recently entered the medical field, but the level of readiness of medical students for it is not obvious. A tool with appropriate psychometric properties for use in different languages and for internationa...