Pediatrics

Cancer Phenotype Development: A Literature Review.

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

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 ...

Correlation between sonographic follow-up of follicular growth, serum and salivary estradiol in women undergoing controlled ovarian stimulation (IVF/ICSI).

AIM OF THE STUDY: Investigation of the correlation between serum estradiol (E2), salivary E2 and son...

[Preconceived ideas about artificial intelligence].

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

Leveraging Human Genetics to Guide Cancer Drug Development.

PURPOSE: The high attrition rate of cancer drug development programs is a barrier to realizing the p...

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...

[Astragalus polysaccharide combined with cisplatin inhibits growth of recurrent tumor and down-regulats the expression of CD44, CD62P and osteopontin in tumor tissues in mice bearing Lewis lung cancer].

Objective To investigate the effects of Astragalus polysaccharide (APS) combined with cisplatin (DDP...

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...

Analysis of the advantages and disadvantages in application of oxygen-driven aerosol and aerosol inhalation by air compressor for the pediatric asthma.

Present study is done to analyze the advantages and disadvantages in application of oxygen-driven ae...

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...

Artificial Intelligence in Pediatric Critical Care Medicine: Are We (Finally) Ready?

Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task.

OBJECTIVE: We executed the Social Media Mining for Health (SMM4H) 2017 shared tasks to enable the co...

Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to pred...

[The development of ophthalmology in artificial intelligence era].

Ophthalmology is a discipline that is highly dependent on the development of technology. Artificial ...

Antifibrinolytic Therapy in Surgery for Adolescent Idiopathic Scoliosis Does the Level 1 Evidence Translate to Practice?

INTRODUCTION: Previous randomized controlled trials have demonstrated the efficacy of antifibrinolyt...

Investigating the Impact of CNN Depth on Neonatal Seizure Detection Performance.

This study presents a novel, deep, fully convolutional architecture which is optimized for the task ...

Anatomical Biomarkers for Adolescent Major Depressive Disorder from Diffusion Weighted Imaging using SVM Classifier.

Adolescent Major Depressive Disorder (MDD) is a common and serious mental illness that could lead to...

Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM.

Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is...

Striking the Right Balance-Applying Machine Learning to Pediatric Critical Care Data.

Applying Machine Learning to Pediatric Critical Care Data.

OBJECTIVES: To explore whether machine learning applied to pediatric critical care data could discov...