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Construction and evaluation of a height prediction model for children with growth disorders treated with recombinant human growth hormone.
BMC endocrine disorders
Jul 9, 2025
BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.
Feasibility study of "double-low" scanning protocol combined with artificial intelligence iterative reconstruction algorithm for abdominal computed tomography enhancement in patients with obesity.
BMC medical imaging
Jul 9, 2025
OBJECTIVE: To evaluate the efficacy of the "double-low" scanning protocol combined with the artificial intelligence iterative reconstruction (AIIR) algorithm for abdominal computed tomography (CT) enhancement in obese patients and to identify the opt...
A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.
BMC medical imaging
Jul 9, 2025
BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomography (NCCT) serves as the primary imaging modality for diagnosing acute ischemic stroke. However, due to the small density difference between the infa...
Longitudinal studies on breastfeeding among preterm infants: a scoping review.
BMC pregnancy and childbirth
Jul 9, 2025
AIM: This study aims to assess the exclusive breastfeeding rate among preterm infants, examine the factors influencing breastfeeding practices, and identify evidence-based interventions to enhance lactation support.
Applying deep learning techniques to identify tonsilloliths in panoramic radiography.
Scientific reports
Jul 9, 2025
Tonsilloliths can be seen on panoramic radiographs (PRs) as deposits located on the middle portion of the ramus of the mandible. Although tonsilloliths are clinically harmless, the high risk of misdiagnosis leads to unnecessary advanced examinations ...
Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images.
Scientific reports
Jul 9, 2025
Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of disease. The greatest challenges today are the repetitive and time-consuming process of interpreting these complex MR images and the problem of unequal diag...
An interpretable dynamic ensemble selection multiclass imbalance approach with ensemble imbalance learning for predicting road crash injury severity.
Scientific reports
Jul 9, 2025
Accurate prediction of crash injury severity and understanding the seriousness of multi-classification injuries is vital for informing authorities and the public. This Knowledge is crucial for enhancing road safety and reducing congestion, as differe...
Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.
Scientific reports
Jul 9, 2025
Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing significant challenges in providing appropriate care. As the number of dementia cases continues to rise, delivering optimal care becomes more complex. ...
Machine learning models for predicting multimorbidity trajectories in middle-aged and elderly adults.
Scientific reports
Jul 9, 2025
Multimorbidity has emerged as a significant public health issue in the context of global population aging. Predicting and managing the progression of multimorbidity in the elderly population is crucial. This study aims to develop predictive models fo...
Diagnosing facial synkinesis using artificial intelligence to advance facial palsy care.
Scientific reports
Jul 9, 2025
Facial palsy (FP) can lead to significant psychological and physical burdens such as facial synkinesis. This involuntary simultaneous movement of facial musculature remains challenging to diagnose and treat. This study aimed to develop a cost-effecti...
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