AIMC Topic: Adolescent

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A deep learning model for differentiating paediatric intracranial germ cell tumour subtypes and predicting survival with MRI: a multicentre prospective study.

BMC medicine
BACKGROUND: The pretherapeutic differentiation of subtypes of primary intracranial germ cell tumours (iGCTs), including germinomas (GEs) and nongerminomatous germ cell tumours (NGGCTs), is essential for clinical practice because of distinct treatment...

A Predictive Model of Pressure Injury in Children Undergoing Living Donor Liver Transplantation Based on Machine Learning Algorithm.

Journal of advanced nursing
AIMS: The aim of our study was to formulate and validate a prediction model using machine learning algorithms to forecast the risk of pressure injuries (PIs) in children undergoing living donor liver transplantation (LDLT).

Effect of machine learning models on clinician prediction of postoperative complications: the Perioperative ORACLE randomised clinical trial.

British journal of anaesthesia
BACKGROUND: Anaesthesiologists might be able to mitigate risk if they know which patients are at greatest risk for postoperative complications. This trial examined the impact of machine learning models on clinician risk assessment.

Siamese based deep neural network for ADHD detection using EEG signal.

Computers in biology and medicine
BACKGROUND: Detecting Attention-Deficit/Hyperactivity Disorder (ADHD) in children is crucial for timely intervention and personalized treatment.

MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated moti...

Etiological stratification and prognostic assessment of haemophagocytic lymphohistiocytosis by machine learning on onco-mNGS data and clinical data.

Frontiers in immunology
INTRODUCTION: Hemophagocytic lymphohistiocytosis (HLH) is a rare, complicated and life threatening hyperinflammatory syndrome that maybe triggered by various infectious agents, malignancies and rheumatologic disorders. Early diagnosis and identificat...

A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.

Journal of clinical epidemiology
OBJECTIVE: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteristics, along with limited physician awareness of the disease's early symptoms. Early and accurate di...

Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.

Journal of sport & exercise psychology
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training int...

Plasma cell-free RNA signatures of inflammatory syndromes in children.

Proceedings of the National Academy of Sciences of the United States of America
Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circul...

A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

JAMA health forum
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...