Background: Hypoxia is an important risk factor and indicator for the declining health of
inpatients. Predicting future hypoxic events using machine learning is a prospective area of …

Hypoxemia is a significant driver of mortality and poor clinical outcomes in conditions such
as brain injury and cardiac arrest in critically ill patients, including COVID-19 patients. Given …

Hypoxemic events are commonly experienced in preterm infants while in a Neonatal
Intensive Care Unit (NICU). These events can contribute to a range of adverse outcomes …

We present an end-to-end model using streaming physiological time series to predict near-
term risk for hypoxemia, a rare, but life-threatening condition known to cause serious patient …

Every year, about 15 million infants are born prematurely, and approximately 1 million child
deaths are related to complications of preterm birth. Cardiorespiratory events, defined as …

Measuring oxygen in blood with a standard imaging method is challenging. Most of the
conventional imaging systems presented outcomes of microcirculatory change …

A method of explaining a machine learning model, including: receiving a plurality of disease
states for a patient over time from a database, wherein the disease states have a plurality of …

(57) ABSTRACT A method of explaining a machine learning model, including: receiving a
plurality of disease states for a patient over time from a database, wherein the disease states …