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Математический метод распознавания образов применительно к задачам диагностики, прогнозирования и классификации в области сердечно – сосудистой хирургии

Математический метод распознавания образов применительно к задачам диагностики, прогнозирования и классификации в области сердечно – сосудистой хирургии

Abstract

Медицина всегда была и до настоящего времени остается во многом наукой эмпирической, оперирующей огромными массивами информации, значительная часть которой слабо формализуется и в ряде случаев не может быть представлена в количественной форме. На сегодняшний день методы распознавания образов (РО) находят практическое применение в различных областях человеческой деятельности везде, где одной из основных задач, стоящих перед человеком, является классификация некоторых объектов или явлений, которым можно сопоставить их формализованное описание.

Medicine always was and to the present tense remains in a great deal science empiric, operating the enormous arrays of information considerable part of which poorlyformalizuetsya and in a number of cases can not be presented in a quantitative form. To date the methods of recognition of patterns (REALTOR) find practical application in the different areas of human activity anywhere that to one of basic tasks, standings before a man, there is classification of some objects or phenomena.

Keywords

АМТ автоматизация медицинской технологии, МРО – методы распознавания образов.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average