AIMC Topic: Child

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Real-time machine learning classification of pallidal borders during deep brain stimulation surgery.

Journal of neural engineering
OBJECTIVE: Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) in patients with Parkinson's disease and dystonia improves motor symptoms and quality of life. Traditionally, pallidal borders have been demarcated by electr...

Predictive validity of radiographic signs of complete discoid lateral meniscus in children using machine learning techniques.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
The diagnostic utility of radiographic signs of complete discoid lateral meniscus remains controversial. This study aimed to investigate the diagnostic accuracy and determine which sign is most reliably detects the presence of a complete discoid late...

Artificial intelligence, machine learning and the pediatric airway.

Paediatric anaesthesia
Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from...

A Multidimensional Neural Maturation Index Reveals Reproducible Developmental Patterns in Children and Adolescents.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Adolescence is a time of extensive neural restructuring, leaving one susceptible to atypical development. Although neural maturation in humans can be measured using functional and structural MRI, the subtle patterns associated with the initial stages...

A Convolutional Neural Network for Real Time Classification, Identification, and Labelling of Vocal Cord and Tracheal Using Laryngoscopy and Bronchoscopy Video.

Journal of medical systems
BACKGROUND: The use of artificial intelligence, including machine learning, is increasing in medicine. Use of machine learning is rising in the prediction of patient outcomes. Machine learning may also be able to enhance and augment anesthesia clinic...

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

BMC medical informatics and decision making
OBJECTIVE: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated...

A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

PloS one
'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim ...

Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer.

International journal of medical informatics
BACKGROUND: The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for experienced multidisciplinary cent...

Gender and active travel: a qualitative data synthesis informed by machine learning.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Innovative approaches are required to move beyond individual approaches to behaviour change and develop more appropriate insights for the complex challenge of increasing population levels of activity. Recent research has drawn on social p...