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  • An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that must be evaluated and assigned to a particular pathology during the diagnostic process. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligence methods (especially computer aided diagnosis and artificial neural networks) can be employed. These adaptive learning algorithms can handle diverse types of medical data and integrate them into categorized outputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificial neural networks in medical diagnosis through selected examples.
  • An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that must be evaluated and assigned to a particular pathology during the diagnostic process. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligence methods (especially computer aided diagnosis and artificial neural networks) can be employed. These adaptive learning algorithms can handle diverse types of medical data and integrate them into categorized outputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificial neural networks in medical diagnosis through selected examples. (en)
Title
  • Artificial neural networks in medical diagnosis
  • Artificial neural networks in medical diagnosis (en)
skos:prefLabel
  • Artificial neural networks in medical diagnosis
  • Artificial neural networks in medical diagnosis (en)
skos:notation
  • RIV/00216224:14110/13:00065996!RIV14-MSM-14110___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(EE2.3.20.0185), P(GA202/07/1669), Z(MSM0021622411), Z(MSM0021622430)
http://linked.open...iv/cisloPeriodika
  • 2
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  • 62141
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14110/13:00065996
http://linked.open...riv/jazykVysledku
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  • medical diagnosis; artificial intelligence; artificial neural networks; cancer; cardiovascular diseases; diabetes (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [48D08FEAF133]
http://linked.open...i/riv/nazevZdroje
  • Journal of Applied Biomedicine
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  • 11
http://linked.open...iv/tvurceVysledku
  • Amato, Filippo
  • Havel, Josef
  • Hampl, Aleš
  • Peña-Méndez, Eladia María
  • López Rodríguez, Alberto
  • Vaňhara, Petr
http://linked.open...ain/vavai/riv/wos
  • 000314809600001
http://linked.open...n/vavai/riv/zamer
issn
  • 1214-021X
number of pages
http://bibframe.org/vocab/doi
  • 10.2478/v10136-012-0031-x
http://localhost/t...ganizacniJednotka
  • 14110
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