OBJECTIVE: SpinePose was developed in 2024 as a novel artificial intelligence (AI) tool to automatically predict spinopelvic parameters with high accuracy and without the need for manual entry. The authors' published results demonstrated excellent pe...
BACKGROUND: Machine-learning models directly predicting iron biomarkers after blood donation could help to manage donation-associated iron deficiency and avoid low haemoglobin deferrals. No such models have been externally validated internationally. ...
PURPOSE: In India, 4.80 million people are blind, and 4.69 million have severe visual impairment. Globally, the digital era and the advent of artificial intelligence devices offer solutions for daily challenges faced by the visually impaired, but the...
This study employs Convolutional Neural Networks (CNNs) as feature extractors with appended regression layers for the non-invasive prediction of Cobb Angle (CA) from Surface Topography (ST) scans in adolescents with Idiopathic Scoliosis (AIS). The ai...
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...
The journal of evidence-based dental practice
Jun 1, 2025
INTRODUCTION: External apical root resorption (EARR) is an undesirable loss of hard tissues of the tooth root frequently affecting to the maxillary incisors. The magnitude of orthodontic forces is a major treatment-related factor associated with EARR...
The increasing integration of artificial intelligence (AI) in social media platforms has transformed digital interactions, particularly among adolescents. AI-driven algorithms curate highly personalized content, reinforcing behavioral patterns and op...
BACKGROUND: Waitlist mortality remains a critical issue for pediatric heart transplant (HTx) candidates, particularly for candidates with congenital heart disease. Listing center organ offer acceptance practices have been identified as a factor influ...
Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS-42 are time-consuming in responding and scoring. We used a novel advanced machine learning approach...
Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issues in those with depression. However, fewer studies have focused on the predictors of SA in adolescen...
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