A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Bayesian approach predicts brain-age from EEG sleep states across age.
Extremely preterm infants commonly require intubation and invasive mechanical ventilation after birth. While the duration of mechanical ventilation should be minimized in order to avoid complications, extubation failure is associated with increases in morbidities and mortality. As part of a prospective observational st…
Improved preterm prediction using synthetic EHG signals.
Deep learning predicts preterm birth risk with improved accuracy.
We describe an application of machine learning to the problem of predicting preterm birth. We conduct a secondary analysis on a clinical trial dataset collected by the National In- stitute of Child Health and Human Development (NICHD) while focusing our attention on predicting different classes of preterm birth. We com…
Preterm births occur at an alarming rate of 10-15%. Preemies have a higher risk of infant mortality, developmental retardation and long-term disabilities. Predicting preterm birth is difficult, even for the most experienced clinicians. The most well-designed clinical study thus far reaches a modest sensitivity of 18.2-…
Paper improves preterm birth prediction using neural networks with noisy labels.
Study shows over-sampling biases prediction results on imbalanced datasets.
Every year, 3 million newborns die within the first month of life. Birth asphyxia and other breathing-related conditions are a leading cause of mortality during the neonatal phase. Current diagnostic methods are too sophisticated in terms of equipment, required expertise, and general logistics. Consequently, early dete…
Data science predicts user interest for midwifery content.
After birth, extremely preterm infants often require specialized respiratory management in the form of invasive mechanical ventilation (IMV). Protracted IMV is associated with detrimental outcomes and morbidities. Premature extubation, on the other hand, would necessitate reintubation which is risky, technically challe…
Extremely preterm infants often require endotracheal intubation and mechanical ventilation during the first days of life. Due to the detrimental effects of prolonged invasive mechanical ventilation (IMV), clinicians aim to extubate infants as soon as they deem them ready. Unfortunately, existing strategies for predicti…
Study improves infant cry-based asphyxia diagnosis using transfer learning.
App enhances midwives' skills in low-income countries.
Taking inspiration from biological evolution, we explore the idea of "Can deep neural networks evolve naturally over successive generations into highly efficient deep neural networks?" by introducing the notion of synthesizing new highly efficient, yet powerful deep neural networks over successive generations via an ev…
3D CNN accurately classifies infant neurodevelopmental age from MRI scans.
SigTime learns interpretable signatures from time series data.
New methods estimate causal effects through mediators, handling confounding without strict assumptions.
Automated GMA using accelerometers detects abnormal infant movements with human-level accuracy.
Hippocampal dentate granule cells are among the few neuronal cell types generated throughout adult life in mammals. In the normal brain, new granule cells are generated from progenitors in the subgranular zone and integrate in a typical fashion. During the development of epilepsy, granule cell integration is profoundly…
Study introduces a new method to estimate causal mediation with multiple mediators.
The paper uses learned prototypes to explain deep learning models for time-series data.
FUALA improves Federated Learning for EHR data, enhancing model uncertainty.