Feature (computer vision)In computer vision and , a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
Cardiac monitoringCardiac monitoring generally refers to continuous or intermittent monitoring of heart activity to assess a patient's condition relative to their cardiac rhythm. Cardiac monitoring is usually carried out using electrocardiography, which is a noninvasive process that records the heart's electrical activity and displays it in an electrocardiogram. It is different from hemodynamic monitoring, which monitors the pressure and flow of blood within the cardiovascular system. The two may be performed simultaneously on critical heart patients.
BradycardiaBradycardia (also sinus bradycardia) is a slow resting heart rate, commonly under 60 beats per minute (BPM) as determined by an electrocardiogram. It is considered to be a normal heart rate during sleep, in young and healthy or elderly adults, and in athletes. In some people, bradycardia below 60 BPM may be associated with fatigue, weakness, dizziness, sweating, and fainting. The term "relative bradycardia" is used to refer to a heart rate slower than an individual's typical resting heart rate.
Signal-averaged electrocardiogramSignal-averaged electrocardiography (SAECG) is a special electrocardiographic technique, in which multiple electric signals from the heart are averaged to remove interference and reveal small variations in the QRS complex, usually the so-called "late potentials". These may represent a predisposition towards potentially dangerous ventricular tachyarrhythmias. A resting electrocardiogram (ECG) is recorded in the supine position using an ECG machine equipped with SAECG software; this can be done by a physician, nurse, or medical technician.
Inappropriate sinus tachycardiaInappropriate sinus tachycardia (IST) is a type of cardiac arrhythmia. Inappropriate sinus tachycardia is caused by electrical signals in the body speeding up the heart, rather than a physical deformity of the heart. This may be caused by a disturbance and/or failure of the autonomic nervous system. Research into the mechanism and etiology (cause) of inappropriate sinus tachycardia is ongoing. While sinus tachycardia is very common and is the most common type of tachycardia, it is rare to be diagnosed with Inappropriate Sinus Tachycardia as an independent symptom that is not part of a larger condition.
Gallop rhythmA gallop rhythm refers to a (usually abnormal) rhythm of the heart on auscultation. It includes three or four sounds, thus resembling the sounds of a gallop. The normal heart rhythm contains two audible heart sounds called S1 and S2 that give the well-known "lub-dub" rhythm; they are caused by the closing of valves in the heart. The first heart sound (S1) is closure of the valve at the end of ventricular filling (the tricuspid and mitral valves); the second heart sound (S2), is closure of the aortic and/or the pulmonary valves as the ventricles relax.
Nonlinear dimensionality reductionNonlinear dimensionality reduction, also known as manifold learning, refers to various related techniques that aim to project high-dimensional data onto lower-dimensional latent manifolds, with the goal of either visualizing the data in the low-dimensional space, or learning the mapping (either from the high-dimensional space to the low-dimensional embedding or vice versa) itself. The techniques described below can be understood as generalizations of linear decomposition methods used for dimensionality reduction, such as singular value decomposition and principal component analysis.
ExperimentAn experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies.
Statistical classificationIn statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation (or observations) belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient (sex, blood pressure, presence or absence of certain symptoms, etc.). Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features.
Feature (machine learning)In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural features such as strings and graphs are used in syntactic pattern recognition. The concept of "feature" is related to that of explanatory variable used in statistical techniques such as linear regression.
