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They are useful in the field of natural language processing and computational text analysis. [2] While the value of the cells is commonly the raw count of a given term, there are various schemes for weighting the raw counts such as row normalizing (i.e. relative frequency/proportions) and tf-idf.
For example, the complete blood count can help a physician to determine why a patient feels unwell and what to do to help. Cell counts within liquid media (such as blood, plasma, lymph, or laboratory rinsate) are usually expressed as a number of cells per unit of volume, thus expressing a concentration (for example, 5,000 cells per milliliter).
The main concepts are those of a grid of cells, called a sheet, with either raw data, called values, or formulas in the cells. Formulas say how to mechanically compute new values from existing values. Values are general numbers, but can also be pure text, dates, months, etc. Extensions of these concepts include logical spreadsheets.
The statistical treatment of count data is distinct from that of binary data, in which the observations can take only two values, usually represented by 0 and 1, and from ordinal data, which may also consist of integers but where the individual values fall on an arbitrary scale and only the relative ranking is important. [example needed]
The MCV can be conceptualized as the total volume of a group of cells divided by the number of cells. For a real world sized example, imagine you had 10 small jellybeans with a combined volume of 10 μL. The mean volume of a jellybean in this group would be 10 μL / 10 jellybeans = 1 μL / jellybean. A similar calculation works for MCV ...
The purpose of plate counting is to estimate the number of cells present based on their ability to give rise to colonies under specific conditions of temperature, time, and nutrient medium. Theoretically, one viable cell can give rise to a colony through replication. However, solitary cells are the exception in nature, and in most cases the ...
Arora et al. (2016) [25] explain word2vec and related algorithms as performing inference for a simple generative model for text, which involves a random walk generation process based upon loglinear topic model. They use this to explain some properties of word embeddings, including their use to solve analogies.
One can see red blood cells, several knobby white blood cells including lymphocytes, a monocyte, a neutrophil, and many small disc-shaped platelets. A monocyte count is part of a complete blood count and is expressed either as a percentage of monocytes among all white blood cells or as absolute numbers. Both may be useful, but these cells ...