Pediatrics

Effects of non-facilitated meaningful activities for people with dementia in long-term care facilities: A systematic review.

This systematic review sought to evaluate the effectiveness of non-facilitated meaningful activities for older people with dementia in long-term care facilities. Searches were conducted in PubMed; CINAHL; EMBASE; Web of science; PsycINFO; Cochrane; ProQuest; and ClinicalTrials.gov to identify articles published between January 2004 and October 2019. A total of six studies were included. Results im...

[Robot-Assisted Repeated Fundoplication in Children and Adolescents].

BACKGROUND: Recurrent gastroesophageal reflux symptoms in adolescents and young adults who underwent fundoplication in childhood present a technical challenge for the surgeon. The distal oesophagus and hiatus are difficult to access by laparotomy, the anatomy is modified by the primary procedure, and there are often dense adhesions between important structures. Robot-assisted surgery may be advant...

Learning curve of robot-assisted choledochal cyst excision in pediatrics: report of 60 cases.

BACKGROUND: Little data are available to assess the learning curve for robot-assisted surgery on choledochal cysts. The aim of this current study is t...

A preliminary study to quantitatively evaluate the development of maturation degree for fetal lung based on transfer learning deep model from ultrasound images.

PURPOSE: The evaluation of fetal lung maturity is critical for clinical practice since the lung immaturity is an important cause of neonatal morbidity...

Artificial intelligence and radiomics in pediatric molecular imaging.

In the past decade, a new approach for quantitative analysis of medical images and prognostic modelling has emerged. Defined as the extraction and ana...

The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm.

In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and su...

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this ...

AI in mental health.

With the advent of digital approaches to mental health, modern artificial intelligence (AI), and machine learning in particular, is being used in the ...

Computer-aided diagnosis for fetal brain ultrasound images using deep convolutional neural networks.

PURPOSE: Fetal brain abnormalities are some of the most common congenital malformations that may associated with syndromic and chromosomal malformatio...

Machine learning paradigm for dynamic contrast-enhanced MRI evaluation of expanding bladder.

Delineation of the bladder under a dynamic contrast enhanced (DCE)-MRI protocol requires robust segmentation. However, this method is subject to error...

Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.

BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired cortisol biosynthesis. Treatment includes glucocor...

Envisioning Insight-Driven Learning Based on Thick Data Analytics With Focus on Healthcare.

Detecting and analyzing patient insights from social media enables healthcare givers to better understand what patients want and also to identify thei...

Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables.

Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder presenting with: unusually abrupt onset of obsessive co...

Smart Environments and Social Robots for Age-Friendly Integrated Care Services.

The world is facing major societal challenges because of an aging population that is putting increasing pressure on the sustainability of care. While ...

Anatomical pathology (human structural biopathology) in the era of "Big Data", digitalization, 5G and artificial intelligence: Evolution or Revolution?

A proposal of an updated system of the Organization of Scientific Biomedical Kowledge is presented, integrating the historical achievements in patholo...

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

This study reports the development of an artificial neural network computation model to predict the accumulation of crack density and crack length in ...

Machine Learning to Support Hemodynamic Intervention in the Neonatal Intensive Care Unit.

Hemodynamic support in neonatal intensive care is directed at maintaining cardiovascular wellbeing. At present, monitoring of vital signs plays an ess...

Multi-instance Deep Learning of Ultrasound Imaging Data for Pattern Classification of Congenital Abnormalities of the Kidney and Urinary Tract in Children.

OBJECTIVE: To reliably and quickly diagnose children with posterior urethral valves (PUV), we developed a multi-instance deep learning method to autom...

Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve.

The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility of healthcare and public health preparedness and p...

A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

The microbiome is a new frontier for building predictors of human phenotypes. However, machine learning in the microbiome is fraught with issues of re...