AI Medical Compendium Topic

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Infant, Newborn

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Application of machine learning in identifying risk factors for low APGAR scores.

BMC pregnancy and childbirth
BACKGROUND: Identifying the risk factors for low APGAR scores at birth is critical for improving neonatal outcomes and guiding clinical interventions.

Machine learning assisted noncontact neonatal anthropometry using FMCW radar.

Scientific reports
This study proposes a method for measuring the height and weight of a neonate conveniently, safely, and accurately by applying a convolutional neural network to frequency-modulated continuous-wave (FMCW) radar sensor data. Fifteen neonates, with pare...

Predicting high-need high-cost pediatric hospitalized patients in China based on machine learning methods.

Scientific reports
Rapidly increasing healthcare spending globally is significantly driven by high-need, high-cost (HNHC) patients, who account for the top 5% of annual healthcare costs but over half of total expenditures. The programs targeting existing HNHC patients ...

Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.

PloS one
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

Medicina (Kaunas, Lithuania)
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...

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...

Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning.

Respiratory research
BACKGROUND: Pneumonia is a major threat to the health of children, especially those under the age of five. Mycoplasma  pneumoniae infection is a core cause of pediatric pneumonia, and the incidence of severe mycoplasma pneumoniae pneumonia (SMPP) has...

The role of AI in reducing maternal mortality: Current impacts and future potentials: Protocol for an analytical cross-sectional study.

PloS one
BACKGROUND: Maternal and newborn mortality remains a critical public health challenge, particularly in resource-limited settings. Despite global efforts, Kenya continues to report high maternal mortality rates of over 350 deaths per 100,000 live birt...

Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates.

Scientific reports
Therapeutic hypothermia (TH) significantly reduces mortality and morbidities in neonates with Neonatal Encephalopathy (NE). NE may result in neonatal death and multisystem organ impairment, including acute kidney injury (AKI). Our study aimed to util...