Pediatrics

Benchmarking machine learning models on multi-centre eICU critical care dataset.

Progress of machine learning in critical care has been difficult to track, in part due to absence of...

Artificial Intelligence and Robotics in Nursing: Ethics of Caring as a Guide to Dividing Tasks Between AI and Humans.

Nurses have traditionally been regarded as clinicians that deliver compassionate, safe, and empathet...

Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual i...

Semantic segmentation of cerebrospinal fluid and brain volume with a convolutional neural network in pediatric hydrocephalus-transfer learning from existing algorithms.

BACKGROUND: For the segmentation of medical imaging data, a multitude of precise but very specific a...

Neonatal EEG sleep stage classification based on deep learning and HMM.

OBJECTIVE: Automatic sleep stage scoring is of great importance for investigating sleep architecture...

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Metastasis development represents an important threat for melanoma patients, even when diagnosed at ...

Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries.

The World Health Organization and other institutions are considering Artificial Intelligence (AI) as...

An Ethical Framework for the Design, Development, Implementation, and Assessment of Drones Used in Public Healthcare.

The use of drones in public healthcare is suggested as a means to improve efficiency under constrain...

Fetal growth and gestational age prediction by machine learning.

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study.

BACKGROUND: Preterm birth is a major global health challenge, the leading cause of death in children...

Prediction of response to anti-vascular endothelial growth factor treatment in diabetic macular oedema using an optical coherence tomography-based machine learning method.

PURPOSE: To predict the anti-vascular endothelial growth factor (VEGF) therapeutic response of diabe...

Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists.

Since the last decade, most of our daily activities have become digital. Digital health takes into a...

Robot-assisted laparoscopic diverticulectomy with ureteral reimplantation.

OBJECTIVE: The objective is to describe our experience with robot-assisted laparoscopic diverticulec...

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...

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

BACKGROUND: Recurrent gastroesophageal reflux symptoms in adolescents and young adults who underwent...

How Will Machine Learning Inform the Clinical Care of Atrial Fibrillation?

Machine learning applications in cardiology have rapidly evolved in the past decade. With the availa...

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 cho...

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 imma...

Development of a QSAR model to predict hepatic steatosis using freely available machine learning tools.

There are various types of hepatic steatosis of which non-alcoholic fatty liver disease, which may b...

Artificial intelligence and radiomics in pediatric molecular imaging.

In the past decade, a new approach for quantitative analysis of medical images and prognostic modell...

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 int...