ELIZA

return kwic search for factors out of >500 occurrences
295043 occurrences (No.82 in the rank) during 5 years in the PubMed. [cache]

327) Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy.

--- ABSTRACT ---

PMID:24304230 DOI:10.1080/17457300.2013.857695

2015 International journal of injury control and safety promotion

* Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

- Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

--- ABSTRACT END ---

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[frequency of next (right) word to factors]

(1)62 for	(12)10 related	(23)3 using	(34)2 during
(2)44 null	(13)8 on	(24)3 which	(35)2 from
(3)36 that	(14)7 have	(25)3 with	(36)2 including
(4)34 associated	(15)7 such	(26)2 (age,	(37)2 independently
(5)31 and	(16)6 may	(27)2 along	(38)2 involved
(6)29 in	(17)4 influence	(28)2 as	(39)2 jointly
(7)20 were	(18)4 significantly	(29)2 c-Jun	(40)2 other
(8)14 influencing	(19)4 to	(30)2 can	(41)2 produced
(9)13 are	(20)3 across	(31)2 contribute	(42)2 was
(10)13 of	(21)3 among	(32)2 contributing
(11)10 affecting	(22)3 like	(33)2 diagnostic

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--- WordNet output for factors --- Overview of noun factor The noun factor has 7 senses (first 4 from tagged texts) 1. (31) factor -- (anything that contributes causally to a result; "a number of factors determined the outcome") 2. (8) component, constituent, element, factor, ingredient -- (an abstract part of something; "jealousy was a component of his character"; "two constituents of a musical composition are melody and harmony"; "the grammatical elements of a sentence"; "a key factor in her success"; "humor: an effective ingredient of a speech") 3. (4) divisor, factor -- (one of two or more integers that can be exactly divided into another integer; "what are the 4 factors of 6?") 4. (1) agent, factor, broker -- (a businessman who buys or sells for another in exchange for a commission) 5. factor -- (any of the numbers (or symbols) that form a product when multiplied together) 6. factor -- (an independent variable in statistics) 7. gene, cistron, factor -- ((genetics) a segment of DNA that is involved in producing a polypeptide chain; it can include regions preceding and following the coding DNA as well as introns between the exons; it is considered a unit of heredity; "genes were formerly called factors") Overview of verb factor The verb factor has 3 senses (first 1 from tagged texts) 1. (2) factor, factor in, factor out -- (resolve into factors; "a quantum computer can factor the number 15") 2. factor -- (be a contributing factor; "make things factor into a company's profitability") 3. factor, factor in, factor out -- (consider as relevant when making a decision; "You must factor in the recent developments") --- WordNet end ---