AI Medical Compendium Topic:
Infant

Clear Filters Showing 631 to 640 of 880 articles

Prenatal exposure to persistent organic pollutants in Northern Tanzania and their distribution between breast milk, maternal blood, placenta and cord blood.

Environmental research
Human exposure to persistent organic pollutants (POPs) begins during pregnancy and may cause adverse health effects in the fetus or later in life. The present study aimed to assess prenatal POPs exposure to Tanzanian infants and evaluate the distribu...

Artificial Intelligence-Assisted Auscultation of Heart Murmurs: Validation by Virtual Clinical Trial.

Pediatric cardiology
Artificial intelligence (AI) has potential to improve the accuracy of screening for valvular and congenital heart disease by auscultation. However, despite recent advances in signal processing and classification algorithms focused on heart sounds, cl...

Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma.

PloS one
We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e.g., a risk stratification schema to improve prognostic profiling. We present the first application ...

Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition.

PloS one
Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ult...

Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.

Iranian journal of allergy, asthma, and immunology
Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food allergy is thought to play an important role in the pathophysiology of EOE. The aim of this study is to evaluate demographic features and sensitivity o...

Dynamic changes in specific anti-L-asparaginase antibodies generation during acute lymphoblastic leukemia treatment.

Pharmacological reports : PR
BACKGROUND: L-asparaginase (L-asp) remains one of the key components of acute lymphoblastic leukemia therapy. Immune reactions to the drug are associated with its diminished activity. The aim of the study was to determine the level of IgM, IgG and Ig...

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

PLoS medicine
BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access...

Ossification area localization in pediatric hand radiographs using deep neural networks for object detection.

PloS one
BACKGROUND: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but thei...

Chest Radiographs in Congestive Heart Failure: Visualizing Neural Network Learning.

Radiology
Purpose To examine Generative Visual Rationales (GVRs) as a tool for visualizing neural network learning of chest radiograph features in congestive heart failure (CHF). Materials and Methods A total of 103 489 frontal chest radiographs in 46 712 pati...

A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.

Journal of medical systems
Skeletal bone age assessment is a widely used standard procedure in both disease detection and growth prediction for children in endocrinology. Conventional manual assessment methods mainly rely on personal experience in observing X-ray images of lef...