Pediatrics

Socially Assistive Robots for Helping Pediatric Distress and Pain: A Review of Current Evidence and Recommendations for Future Research and Practice.

OBJECTIVES: Interacting with socially assistive robots (SAR) has been shown to influence human behav...

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.

BACKGROUND: Tracking and predicting the growth performance of plants in different environments is cr...

The Role of the ACR Data Science Institute in Advancing Health Equity in Radiology.

Commercially available artificial intelligence (AI) algorithms outside of health care have been show...

Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice.

Artificial Intelligence (AI) and access to "Big Data" together with the evolving techniques in biote...

Artificial intelligence estimates the impact of human papillomavirus types in influencing the risk of cervical dysplasia recurrence: progress toward a more personalized approach.

The objective of this study was to determine whether the pretreatment human papillomavirus (HPV) gen...

Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates.

OBJECTIVE: To develop and validate a new risk score for intraventricular hemorrhage (IVH) in preterm...

Childhood Asthma: Advances Using Machine Learning and Mechanistic Studies.

A paradigm shift brought by the recognition that childhood asthma is an aggregated diagnosis that co...

Artificial intelligence - The next frontier in pediatric dentistry.

Cancer Phenotype Development: A Literature Review.

EHR-based, computable phenotypes can be leveraged by healthcare organizations and researchers to imp...

Socially Assistive Robots (SAR) in In-Patient Care for the Elderly.

In-patient care of the elderly is currently being put to the test in all developed industrial nation...

A Phenotypic Description of Congenital Myotonic Dystrophy using PhenoStacks.

BACKGROUND: Congenital Myotonic Dystrophy (CDM1) is a rare neuromuscular condition caused by a tripl...

Three Problems with Big Data and Artificial Intelligence in Medicine.

The rise of big data and artificial intelligence (AI) in health care has engendered considerable exc...

Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications.

Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional f...

Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature.

Karakurt N, Uslu İ, Aygün C, Albayrak C. Hematological disturbances in Down syndrome: single centre ...

Evaluation of Cyclosporine Pharmacokinetic, Monitoring, and Dosing Parameters for GVHD Prophylaxis in Hematopoietic Stem Cell Transplant (HSCT) Recipients.

Allogeneic hematopoietic stem cell transplantation (AHSCT) is a major method of treatment for differ...

Prediction of Transient or Permanent Congenital Hypothyroidism from Initial Thyroid Stimulating Hormone Levels.

OBJECTIVE: To identify factors that discriminate between transient and permanent congenital hypothyr...

The role of artificial intelligence in orthopaedic surgery.

Despite significant advances in orthopaedic surgery, variability still exists between providers and ...

Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit.

OBJECTIVE: Quantify physiologically acceptable PICU-discharge vital signs and develop machine learni...

Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care.

Digital health constitutes a merger of both software and hardware technology with health care delive...

[Preconceived ideas about artificial intelligence].

Preconceived ideas about artificial intelligence. Artificial intelligence (AI) has made considerable...

Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury.

OBJECTIVEModern surgical planning and prognostication requires the most accurate outcomes data to pr...