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Found 9 papers, 2 papers with code
Learning domain-invariant classifiers for infant cry sounds
The issue of domain shift remains a problematic phenomenon in most real-world datasets and clinical audio is no exception.
A cry for help: Early detection of brain injury in newborns
Since the 1960s, neonatal clinicians have known that newborns suffering from certain neurological conditions exhibit altered crying patterns such as the high-pitched cry in birth asphyxia.
CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds
This paper describes the Ubenwa CryCeleb dataset - a labeled collection of infant cries - and the accompanying CryCeleb 2023 task, which is a public speaker verification challenge based on cry sounds.
A Fully Tensorized Recurrent Neural Network
Recurrent neural networks (RNNs) are powerful tools for sequential modeling, but typically require significant overparameterization and regularization to achieve optimal performance.
Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia
Despite continuing medical advances, the rate of newborn morbidity and mortality globally remains high, with over 6 million casualties every year.
Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing
Extremely preterm infants commonly require intubation and invasive mechanical ventilation after birth.
A Semi-Markov Chain Approach to Modeling Respiratory Patterns Prior to Extubation in Preterm Infants
After birth, extremely preterm infants often require specialized respiratory management in the form of invasive mechanical ventilation (IMV).
Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants
Extremely preterm infants often require endotracheal intubation and mechanical ventilation during the first days of life.
Ubenwa: Cry-based Diagnosis of Birth Asphyxia
Every year, 3 million newborns die within the first month of life.
