AIMC Topic: Pediatrics

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Artificial intelligence in paediatric radiology: Future opportunities.

The British journal of radiology Sep 17, 2020
Artificial intelligence (AI) has received widespread and growing interest in healthcare, as a method to save time, cost and improve efficiencies. The high-performance statistics and diagnostic accuracies reported by using AI algorithms (with respect ...
Diagnostic Imaging Radiology Pediatrics Image Interpretation, Computer-Assisted Humans Artificial Intelligence Clinical Decision-Making Child
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Learning curve of robot-assisted choledochal cyst excision in pediatrics: report of 60 cases.

Surgical endoscopy Jun 15, 2020
BACKGROUND: Little data are available to assess the learning curve for robot-assisted surgery on choledochal cysts. The aim of this current study is to investigate the characteristics of the learning curve for robot-assisted choledochal cyst excision...
Humans Learning Curve Robotics Choledochal Cyst Laparoscopy Anastomosis, Roux-en-Y Retrospective Studies Pediatrics Child Treatment Outcome
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Artificial intelligence and radiomics in pediatric molecular imaging.

Methods (San Diego, Calif.) Jun 13, 2020
In the past decade, a new approach for quantitative analysis of medical images and prognostic modelling has emerged. Defined as the extraction and analysis of a large number of quantitative parameters from medical images, radiomics is an evolving fie...
Pediatrics Medical Oncology Datasets as Topic Patient Care Planning Triage Humans Prognosis Telemedicine Neural Networks, Computer Reproducibility of Results Molecular Imaging Child Image Processing, Computer-Assisted
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Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.

Neural networks : the official journal of the International Neural Network Society Mar 18, 2020
Emergency department (ED) overcrowding is a global condition that severely worsens attention to patients, increases clinical risks and affects hospital cost management. A correct and early prediction of ED's admission is of high value and a motivatio...
Hospitalization Male Infant Deep Learning Forecasting Databases, Factual Female Emergency Service, Hospital Pediatrics Patient Admission Cohort Studies Child, Preschool Child Triage Humans Neural Networks, Computer
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Predicting Wait Times in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Patient perceptions of wait time during outpatient office visits can affect patient satisfaction. Providing accurate information about wait times could improve patients' satisfaction by reducing uncertainty. However, these are rarely known about effi...
Time-to-Treatment Machine Learning Humans Pediatrics Time Factors Models, Statistical Patient Satisfaction ROC Curve Ophthalmology Linear Models Supervised Machine Learning Ambulatory Care Facilities
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Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap.

Clinical pharmacology and therapeutics Jan 22, 2020
Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real-world data from electronic heal...
Child Randomized Controlled Trials as Topic Pediatrics Inventions Evidence-Based Medicine Humans Artificial Intelligence Machine Learning Data Science
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Artificial intelligence applications for pediatric oncology imaging.

Pediatric radiology Oct 16, 2019
Machine learning algorithms can help to improve the accuracy and efficiency of cancer diagnosis, selection of personalized therapies and prediction of long-term outcomes. Artificial intelligence (AI) describes a subset of machine learning that can id...
Artificial Intelligence Neoplasms Pediatrics Humans
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A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England) Aug 14, 2019
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...
Humans Cohort Studies Retrospective Studies Child, Preschool Critical Illness Child Infant Area Under Curve Republic of Korea ROC Curve Deep Learning Pediatrics Big Data Mortality Adolescent Female Male Risk Assessment
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Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data.

Pediatric transplantation Jul 22, 2019
Machine learning analyses allow for the consideration of numerous variables in order to accommodate complex relationships that would not otherwise be apparent in traditional statistical methods to better classify patient risk. The SPLIT registry data...
Pediatrics Anastomosis, Surgical Liver Failure Predictive Value of Tests Biliary Tract Surgical Procedures Registries Liver Transplantation Child, Preschool Child Adult Humans Treatment Outcome Algorithms Risk Assessment Machine Learning Prospective Studies Infant Software Risk Factors Adolescent Young Adult
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Adjusting the dose in paediatric care: dispersing four different aspirin tablets and taking a proportion.

European journal of hospital pharmacy : science and practice Jun 11, 2019
OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the ward to obtain the right dose. One example is manipulation of tablets containing the slightly water-soluble substance aspirin, used in paediatric care as...
Chromatography, High Pressure Liquid Humans Pediatrics Child Aspirin Tablets
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