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DIAGAID :
DIAGAID : a connectionists approach to determine the information value of clinical data
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- Forsström, Jari (författare)
- University of Turku, Department of Clinical Chemistry, Central Laboratory, Turku University Central Hospital, Turku, Finland
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- Eklund, Patrik, 1958- (författare)
- Department of Computer Science, Åbo Akademi, Åbo, Finland
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- Virtanen, Harry (författare)
- Department of Computer Science, Åbo Akademi, Åbo, Finland
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- Waxlax, Joakim (författare)
- Department of Computer Science, Åbo Akademi, Åbo, Finland
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- Lähdevirta, Juhani (författare)
- Aurora Hospital, Helsinki, Finland
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(creator_code:org_t)
- Elsevier, 1991
- 1991
- Engelska.
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Ingår i: Artificial Intelligence in Medicine. - : Elsevier. - 0933-3657 .- 1873-2860. ; 3:4, s. 193-201
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In clinical medicine the diagnosis is usually based on several signs and symptoms and some laboratory test results. It would be of great benefit if we could learn the diagnostic criteria from example cases and represent systematically the most important findings supporting or rejecting the diagnosis. In rare diseases where the physician may not be familiar with the ailment the scoring of symptoms would be very useful. In this paper we describe a connectionist approach based on Minsky-Papert's perceptrons for evaluation of the information value of clinical data in diagnosing the Nephropathia epidemica. The scores are compared with those from the Bayesian approach and from the evaluation by an experienced clinician.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Neural networks
- perceptron
- expert systems
- diagnosis
- Nephropathia epidemica
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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