AIMC Topic: Neonatal Screening

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Development and validation of a screening model for early diagnosis of biliary atresia in neonates with cholestasis.

Pediatric surgery international
BACKGROUND: Biliary atresia (BA) is a progressive neonatal cholestatic liver disease that requires timely diagnosis and intervention. Differentiating BA from other causes of neonatal cholestasis remains a significant clinical challenge.

Improving newborn screening accuracy through genome sequencing, targeted metabolomics, and machine learning.

BMC medical genomics
BACKGROUND: Newborn screening (NBS) enables early detection of metabolic disorders, but current tandem mass spectrometry (MS/MS) methods often lead to false positives and require confirmatory testing, causing diagnostic delays. We evaluated whether i...

Developing an explainable machine learning model to predict false-negative citrin deficiency cases in newborn screening.

Orphanet journal of rare diseases
BACKGROUND: Neonatal Intrahepatic Cholestasis caused by Citrin Deficiency (NICCD) is an autosomal recessive disorder affecting the urea cycle and energy metabolism. Newborn screening (NBS) usually relies on elevated citrulline, but some patients have...

Neonatal hyperbilirubinemia: past lessons, current practices, and future directions.

European journal of pediatrics
Neonatal hyperbilirubinemia is a common clinical condition that, if not promptly and effectively managed, may lead to rare but severe neurodevelopmental complications. This review traces the historical progression of screening, diagnostic, and therap...

Deep learning approach for screening neonatal cerebral lesions on ultrasound in China.

Nature communications
Timely and accurate diagnosis of severe neonatal cerebral lesions is critical for preventing long-term neurological damage and addressing life-threatening conditions. Cranial ultrasound is the primary screening tool, but the process is time-consuming...

Toward the Development of a Novel Newborn Screening Modality: In-Depth Nontargeted Proteome Analysis of Dried Blood Spots with a Robotic Pipeline Using Low-Cost Iron Powders.

Analytical chemistry
We developed a simple protein extraction method for dried blood spots (DBS) that potentially meets the throughput required for newborn screening (NBS) and optimizes nontargeted proteomic analysis in combination with liquid chromatography coupled mass...

Newborn Pulse-Oximetry Screening.

Clinics in perinatology
Pulse oximetry screening (POS) is a noninvasive tool for the detection of critical congenital heart defects (CCHD) that has moderate sensitivity and high specificity. It is readily accepted by parents and health care professional and has significantl...

Prediction of retinopathy of prematurity development and treatment need with machine learning models.

BMC ophthalmology
BACKGROUND: To evaluate the effectiveness of machine learning (ML) models in predicting the occurrence of retinopathy of prematurity (ROP) and treatment need.

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Scientific reports
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...

AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings.

JAMA network open
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. If detected and treated early, ROP-associated blindness is preventable; however, identifying patients who might respond to treatment requi...