AIMC Topic: Child

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Diffusion histology imaging differentiates distinct pediatric brain tumor histology.

Scientific reports
High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation o...

Fear Recognition for Women Using a Reduced Set of Physiological Signals.

Sensors (Basel, Switzerland)
Emotion recognition is benefitting from the latest research into physiological monitoring and wireless communications, among other remarkable achievements. These technologies can indeed provide solutions to protect vulnerable people in scenarios such...

CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

British journal of haematology
Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identi...

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning.

Computers in biology and medicine
BACKGROUND: Presumed serious infection (PSI) is defined as a blood culture drawn and new antibiotic course of at least 4 days among pediatric patients with Central Venous Lines (CVLs). Early PSI prediction and use of medical interventions can prevent...

Primary vs redo robotic pyeloplasty: A comparison of outcomes.

Journal of pediatric urology
INTRODUCTION: Robot-assisted laparoscopic pyeloplasty (RALP) is a safe and efficacious option for repair of UPJO. We hypothesize that redo-RALP is technically more difficult but has comparable outcomes to primary RALP.

Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study.

European journal of radiology
PURPOSE: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine learning (ML) have proven useful even in absence of a standardized data mining pipeline. We aimed to assess ML diagnostic performance in spinal lesio...

Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.

American journal of ophthalmology
PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL];...

Performance of an artificial intelligence system for bone age assessment in Tibet.

The British journal of radiology
OBJECTIVE: To investigate whether bone age (BA) of children living in Tibet Highland could be accurately assessed using a fully automated artificial intelligence (AI) system.