# algorithm

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## algorithm

[al´go-rithm]
1. a series of algebraic equations.
2. a logical progression that is programmed for a computer.
3. a model for making decisions.
Algorithm. Model of a decision algorithm. ACC/AHA Guidelines for the Management of Patients with Unstable Angina and Non-ST Segment Elevation Myocardial Infarction. JACC 2000, 36: 970-1062. Copyright 2000, by the American College of Cardiology and American Heart Association. Permission granted for one time use. Further reproduction is not permitted without permission of the ACC/AHA.
Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health, Seventh Edition. © 2003 by Saunders, an imprint of Elsevier, Inc. All rights reserved.

## al·go·rithm

(al'gō-ridhm),
A systematic process consisting of an ordered sequence of steps, each step depending on the outcome of the previous one. In clinical medicine, a step-by-step protocol for management of a health care problem; in computed tomography, the formulas used to calculate the final image from the transmitted x-ray data.
[Mediev. L. algorismus, after Muhammad ibn-Musa al-Khwarizmi, Arabian mathematician, + G. arithmos, number]
Farlex Partner Medical Dictionary © Farlex 2012

## algorithm

(1) A sequential procedure for solving a mathematical problem.
(2) A step-by-step procedure for reaching a decision when choosing among multiple alternative options, linked to each other by a decision tree.

## algorithm

Decision-making A logical set of rules for solving a specific problem, which assumes that all of the data is objective, that there are a finite number of solutions to the problem, and that there are logical steps that must be performed to arrive at each of those solutions NIHspeak A step-by-step procedure for solving a problem; a formula. See Back-propagation, Critical pathway, Genetic algorithm, Risk of ovarian cancer algorithm.
McGraw-Hill Concise Dictionary of Modern Medicine. © 2002 by The McGraw-Hill Companies, Inc.

## al·go·rithm

(al'gŏr-idhm)
1. A process consisting of steps, each depending on the outcome of the previous one.
2. clinical medicine A step-by-step protocol for management of a health care problem.
3. computed tomography The formulas used for calculation of the final image from the x-ray transmission data.
[Mediev. L. algorismus, after Muhammad ibn-Musa al-Khwarizmi, Persian mathematician, + G. arithmos, number]
Medical Dictionary for the Health Professions and Nursing © Farlex 2012

## al·go·rithm

(al'gŏr-idhm)
A systematic process consisting of an ordered sequence of steps, each step depending on the outcome of the previous one.
[Mediev. L. algorismus, after Muhammad ibn-Musa al-Khwarizmi, Persian mathematician, + G. arithmos, number]
Medical Dictionary for the Dental Professions © Farlex 2012
References in periodicals archive ?
An example of the ALGATOR's query queryF1C1 = FROM TestSetO WHERE (algorithm-*) AND ComputerID=F1.CI SELECT Tmin AS A1; queryF2C1 = FROM TestSetO WHERE (algorithms) AND ComputerID=F2.CI SELECT Tmin AS A2; FROM queryF1C1, queryF2Cl WHERE (algorithm=JHoare) SELECT N, A1/A2 AS Q 4 Analyzing the results
For example, to get the minimal execution times for algorithms named JHoare and JWirth on the test set called TestSet3, a user can run query as depicted in Figure 2.
This process of adaptive sampling is key to the algorithm's ability to make the right decision at each step.
In experiments, Singer and Balkanski demonstrated that their algorithm could sift through a dataset which contained 1,000,000 ratings from 6,000 users on 4,000 movies and recommend a personalized and diverse collection of movies for an individual user 20 times faster than the state-of-the-art method.
In this section, there will be a discussion about the segmentation algorithms that generate the partial results which are used in our voting algorithms.
The algorithm was selected to compensate for some of the inaccurate results the other algorithms might produce.
Todd is better positioned to effectively use algorithms than Katie or James as he has some key knowledge upon which algorithms are built.
Some of the most commonly used image steganography algorithms are LSB embedding, Pseudo Random Least Significant Bit (PRLSB) embedding, pallet based embedding and quantification based embedding [18-21].
Machine learning algorithms divide into two main categories: supervised learning and unsupervised learning.
This approach is intended to make it suitable for circuit design unlike the NAF conversion algorithms mentioned above.

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