AI Medical Compendium Topic:
Infant

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Machine Learning Supports Automated Digital Image Scoring of Stool Consistency in Diapers.

Journal of pediatric gastroenterology and nutrition
BACKGROUND/AIMS: Accurate stool consistency classification of non-toilet-trained children remains challenging. This study evaluated the feasibility of automated classification of stool consistencies from diaper photos using machine learning (ML).

Machine Learning Applied to Registry Data: Development of a Patient-Specific Prediction Model for Blood Transfusion Requirements During Craniofacial Surgery Using the Pediatric Craniofacial Perioperative Registry Dataset.

Anesthesia and analgesia
BACKGROUND: Craniosynostosis is the premature fusion of ≥1 cranial sutures and often requires surgical intervention. Surgery may involve extensive osteotomies, which can lead to substantial blood loss. Currently, there are no consensus recommendation...

A Deep Neural Network to Distinguish COVID-19 from other Chest Diseases Using X-ray Images.

Current medical imaging
BACKGROUND: Scanning a patient's lungs to detect Coronavirus 2019 (COVID-19) may lead to similar imaging of other chest diseases. Thus, a multidisciplinary approach is strongly required to confirm the diagnosis. There are only a few works targeted at...

[Determination of four bisphenol environmental hormone residues in infant serum by liquid chromatography-tandem mass spectrometry].

Se pu = Chinese journal of chromatography
Bisphenols are important industrial raw materials that are widely used to produce plastic bottles (feeding bottles), infant cups, and food and beverage (milk powder) cans. Because of the estrogen-like effect of bisphenols, even low-dose intake of the...

Clinical application of artificial intelligence-assisted diagnosis using anteroposterior pelvic radiographs in children with developmental dysplasia of the hip.

The bone & joint journal
AIMS: The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an an...

Machine Learning To Predict Serious Bacterial Infections in Young Febrile Infants.

Pediatrics
BACKGROUND: Recent decision rules for the management of febrile infants support the identification of infants at higher risk of serious bacterial infections (SBIs) without the performance of routine lumbar puncture. We derive and validate a model to ...

Augmenting Interpretation of Chest Radiographs With Deep Learning Probability Maps.

Journal of thoracic imaging
PURPOSE: Pneumonia is a common clinical diagnosis for which chest radiographs are often an important part of the diagnostic workup. Deep learning has the potential to expedite and improve the clinical interpretation of chest radiographs. While earlie...

Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence.

Pediatric clinics of North America
Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight and very preterm infants in the United States. With improved survival of smaller babies, more infants are at risk for ROP, yet there is an increasing...

Automatic Machine Learning to Differentiate Pediatric Posterior Fossa Tumors on Routine MR Imaging.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Differentiating the types of pediatric posterior fossa tumors on routine imaging may help in preoperative evaluation and guide surgical resection planning. However, qualitative radiologic MR imaging review has limited performa...

Rigid Cranial Fixation for Robot-Assisted Stereoelectroencephalography in Toddlers: Technical Considerations.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Stereoelectroencephalography (sEEG) using depth electrodes has become a mainstay of pediatric epilepsy surgery. This technique relies on rigid cranial fixation using skull pins, which forms the basis for accurate stereotactic navigation. ...