K-means clusteringk-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. k-means clustering minimizes within-cluster variances (squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances.
Cluster analysisCluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.
Red blood cellRed blood cells (RBCs), also referred to as red cells, red blood corpuscles (in humans or other animals not having nucleus in red blood cells), haematids, erythroid cells or erythrocytes (from Greek erythros 'red' and kytos 'hollow vessel', with -cyte translated as 'cell' in modern usage), are the most common type of blood cell and the vertebrate's principal means of delivering oxygen (O2) to the body tissues—via blood flow through the circulatory system.
Erythrocyte deformabilityErythrocyte deformability refers to the ability of erythrocytes (red blood cells, RBC) to change shape under a given level of applied stress, without hemolysing (rupturing). This is an important property because erythrocytes must change their shape extensively under the influence of mechanical forces in fluid flow or while passing through microcirculation. The extent and geometry of this shape change can be affected by the mechanical properties of the erythrocytes, the magnitude of the applied forces, and the orientation of erythrocytes with the applied forces.
Packed red blood cellsPacked red blood cells, also known as packed cells, are red blood cells that have been separated for blood transfusion. The packed cells are typically used in anemia that is either causing symptoms or when the hemoglobin is less than usually 70–80 g/L (7–8 g/dL). In adults, one unit brings up hemoglobin levels by about 10 g/L (1 g/dL). Repeated transfusions may be required in people receiving cancer chemotherapy or who have hemoglobin disorders. Cross-matching is typically required before the blood is given.
Hierarchical clusteringIn data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two categories: Agglomerative: This is a "bottom-up" approach: Each observation starts in its own cluster, and pairs of clusters are merged as one moves up the hierarchy. Divisive: This is a "top-down" approach: All observations start in one cluster, and splits are performed recursively as one moves down the hierarchy.
BiclusteringBiclustering, block clustering, Co-clustering or two-mode clustering is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin to name a technique introduced many years earlier, in 1972, by John A. Hartigan. Given a set of samples represented by an -dimensional feature vector, the entire dataset can be represented as rows in columns (i.e., an matrix). The Biclustering algorithm generates Biclusters.
Blood bankA blood bank is a center where blood gathered as a result of blood donation is stored and preserved for later use in blood transfusion. The term "blood bank" typically refers to a department of a hospital usually within a Clinical Pathology laboratory where the storage of blood product occurs and where pre-transfusion and Blood compatibility testing is performed. However, it sometimes refers to a collection center, and some hospitals also perform collection.
Erythrocyte fragilityErythrocyte fragility refers to the propensity of erythrocytes (red blood cells, RBC) to hemolyse (rupture) under stress. It can be thought of as the degree or proportion of hemolysis that occurs when a sample of red blood cells are subjected to stress (typically physical stress, and most commonly osmotic and/or mechanical stress). Depending on the application as well as the kind of fragility involved, the amount of stress applied and/or the significance of the resultant hemolysis may vary.
Determining the number of clusters in a data setDetermining the number of clusters in a data set, a quantity often labelled k as in the k-means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain class of clustering algorithms (in particular k-means, k-medoids and expectation–maximization algorithm), there is a parameter commonly referred to as k that specifies the number of clusters to detect.
Blood cellA blood cell, also called a hematopoietic cell, hemocyte, or hematocyte, is a cell produced through hematopoiesis and found mainly in the blood. Major types of blood cells include red blood cells (erythrocytes), white blood cells (leukocytes), and platelets (thrombocytes). Together, these three kinds of blood cells add up to a total 45% of the blood tissue by volume, with the remaining 55% of the volume composed of plasma, the liquid component of blood.
White blood cellWhite blood cells, also called leukocytes or leucocytes, are cells of the immune system that are involved in protecting the body against both infectious disease and foreign invaders. White blood cells include three main subtypes; granulocytes, lymphocytes and monocytes. White cells is most preferred rather than the, white blood cells, because, they spend most of their time in the lymph or plasma. All white blood cells are produced and derived from multipotent cells in the bone marrow known as hematopoietic stem cells.
Clustering high-dimensional dataClustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions equals the size of the vocabulary.
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.
Single-linkage clusteringIn statistics, single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at each step combining two clusters that contain the closest pair of elements not yet belonging to the same cluster as each other. This method tends to produce long thin clusters in which nearby elements of the same cluster have small distances, but elements at opposite ends of a cluster may be much farther from each other than two elements of other clusters.
Whole bloodWhole blood (WB) is human blood from a standard blood donation. It is used in the treatment of massive bleeding, in exchange transfusion, and when people donate blood to themselves. One unit of whole blood (~517 mls) brings up hemoglobin levels by about 10 g/L. Cross matching is typically done before the blood is given. It is given by injection into a vein. Side effects include red blood cell breakdown, high blood potassium, infection, volume overload, lung injury, and allergic reactions such as anaphylaxis.
Nucleated red blood cellA nucleated red blood cell (NRBC), also known by several other names, is a red blood cell that contains a cell nucleus. Almost all vertebrate organisms have hemoglobin-containing cells in their blood, and with the exception of mammals, all of these red blood cells are nucleated. In mammals, NRBCs occur in normal development as precursors to mature red blood cells in erythropoiesis, the process by which the body produces red blood cells. NRBCs are normally found in the bone marrow of humans of all ages and in the blood of fetuses and newborn infants.
Complete blood countA complete blood count (CBC), also known as a full blood count (FBC), is a set of medical laboratory tests that provide information about the cells in a person's blood. The CBC indicates the counts of white blood cells, red blood cells and platelets, the concentration of hemoglobin, and the hematocrit (the volume percentage of red blood cells). The red blood cell indices, which indicate the average size and hemoglobin content of red blood cells, are also reported, and a white blood cell differential, which counts the different types of white blood cells, may be included.
BloodBlood is a body fluid in the circulatory system of humans and other vertebrates that delivers necessary substances such as nutrients and oxygen to the cells, and transports metabolic waste products away from those same cells. Blood in the circulatory system is also known as peripheral blood, and the blood cells it carries, peripheral blood cells. Blood is composed of blood cells suspended in blood plasma.
Scale-invariant feature transformThe scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999. Applications include object recognition, robotic mapping and navigation, , 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. SIFT keypoints of objects are first extracted from a set of reference images and stored in a database.
