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A person taking the test covers one eye from 6 metres or 20 feet away, and reads aloud the letters of each row, beginning at the top. The smallest row that can be read accurately indicates the visual acuity in that specific eye. The symbols on an acuity chart are formally known as "optotypes". Variation of Snellen chart with another letter ...
An eye chart is a chart used to measure visual acuity comprising lines of optotypes in ranges of sizes. Optotypes are the letters or symbols shown on an eye chart. [ 1 ] Eye charts are often used by health care professionals, such as optometrists , physicians and nurses , to screen persons for vision impairment .
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Amsler grid, Chart 1. There are 7 types of Amsler grid charts. All charts measure 10 cm × 10 cm (3.9 in × 3.9 in), which when viewed at a distance of 33 cm (13 in) from the eye can be used to measure defects in the central 20 degrees of the visual field. [3]
A visual field test is an eye examination that can detect dysfunction in central and peripheral vision which may be caused by various medical conditions such as glaucoma, stroke, pituitary disease, brain tumours or other neurological deficits.
to test colour vision ••Ishihara's chart: to determine the type of colour blindness Stenopaeic slit: detection of axis of the cylindrical (astigmatism) power of the eye; glaucoma testing Implants - •Intraocular lens: prosthetic lenses implanted after lens (anatomy) removal •Artificial eyes: as non-functional cosmetic implants into the ...
Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."