AI Medical Compendium Topic

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Investigating the impact of an AI-based play activities intervention on the quality of life of school-aged children with ADHD.

Research in developmental disabilities
BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that not only impacts children's behavior, learning, and social interactions but also their quality of life. Advances in artificial intelligence (A...

Considerations for using tree-based machine learning to assess causation between demographic and environmental risk factors and health outcomes.

Environmental science and pollution research international
Evaluation of the heterogeneous treatment effect (HTE) allows for the assessment of the causal effect of a therapy or intervention while considering heterogeneity in individual factors within a population. Machine learning (ML) methods have previousl...

Trends in brain MRI and CP association using deep learning.

La Radiologia medica
Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative...

A new scoring in differential diagnosis: multisystem inflammatory syndrome or adenovirus infection?

Turkish journal of medical sciences
BACKGROUND/AIM: Differentiating multisystem inflammatory syndrome in children (MIS-C) from adenovirus infection (AI) can be challenging due to similar clinical and laboratory findings. This study aimed to identify distinguishing characteristics and d...

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control.

AI-PEDURO - Artificial intelligence in pediatric urology: Protocol for a living scoping review and online repository.

Journal of pediatric urology
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) methods are increasingly being applied in pediatric urology across a growing number of settings, with more extensive databases and wider interest for use in clinical practice. More th...

Predicting the Risk of Maxillary Canine Impaction Based on Maxillary Measurements Using Supervised Machine Learning.

Orthodontics & craniofacial research
OBJECTIVES: To predict palatally impacted maxillary canines based on maxilla measurements through supervised machine learning techniques.

Tracing the path from preschool wheezing to asthma.

Pediatric pulmonology
This short review illustrates, using two recent studies, the potential and challenges of using machine learning methods to identify phenotypes of wheezing and asthma from childhood onwards.

Towards dental diagnostic systems: Synergizing wavelet transform with generative adversarial networks for enhanced image data fusion.

Computers in biology and medicine
The advent of precision diagnostics in pediatric dentistry is shifting towards ensuring early detection of dental diseases, a critical factor in safeguarding the oral health of the younger population. In this study, an innovative approach is introduc...

Molecular profiling of blood plasma-derived extracellular vesicles derived from Duchenne muscular dystrophy patients through integration of FTIR spectroscopy and machine learning reveals disease signatures.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
PURPOSE: To identify and monitor the FTIR spectral signatures of plasma extracellular vesicles (EVs) from Duchenne Muscular Dystrophy (DMD) patients at different stages with Healthy controls using machine learning models.