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Wyświetlanie 1-3 z 3
Tytuł:
Self optimizing neural network - as expert system in medical heart attack.
Autorzy:
Popa, A.
Wojczyk, S.
Lizis, M.
Powiązania:
https://bibliotekanauki.pl/articles/333471.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
sieci neuronowe
systemy eksperckie
choroby serca
neural network
expert systems
heart diseases
Opis:
The main aim of Self Optimizing Neural Network (SONN), which are presented in this paper, is construction of expert system on the basis of analysis of medical information about group of patients. The expert system is built on the basis of neural network, and the main task of this system is to expect future patient health, based on information about the patient. Such a system can give the doctors a hint about that what can be happen with patient. And what is more important - the SONN construction process is very flexibly and adapts topology and all weights to training data. This is undoubtedly a great advantage of this type of neural network. Moreover the construction process is quite simple. The network topology and all connections between neurons can be easy implemented and kept in such a way, which allows to create very efficient expert system. In this paper we describe the process of construction of neural network which is based on one-shot analysis of learning patterns. On the basis of appropriate computation the SONN topology is built. The construction process can be repeated on the learning group of patients. In this way the expert system (based on SONN) will be better and better.
Źródło:
Journal of Medical Informatics & Technologies; 2008, 12; 77-82
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The dedicated decision support system in recognition of some uncertain disease entities
Autorzy:
Porwik, P.
Powiązania:
https://bibliotekanauki.pl/articles/333041.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie obrazu
klasyfikacja danych
sieci neuronowe
systemy wspomagania decyzji
image recognition
data classification
neural network
decision support systems
Opis:
This work presents the principles of image recognition, where quality-based methods are applied. The neural networks and additional software have been proposed. This goal was achieved by using non-parametric recognition algorithms. In this paper the two-state hybrid classification method has been proposed, where artificial intelligence algorithm is included. In recognition process, the learning method, selection and optimization of diagnostic parameters have been introduced. The integrated part of the classifier structure is voting mechanism, which indicates incorrect states of the system – for example the unrecognized images. Effectiveness of the system has been shown by means of examples, where ambiguous data have been incorporated – it is very often a practice of medical diagnostics.
Źródło:
Journal of Medical Informatics & Technologies; 2009, 13; 97-100
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using artificial immune and case-based reasoning methods in classification of treatment effectiveness
Autorzy:
Badura, D.
Ferdynus, D.
Powiązania:
https://bibliotekanauki.pl/articles/333874.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
wnioskowanie bazujące na przykładach
sztuczne systemy immunologiczne
sieci neuronowe rozmyte
case-based reasoning
artificial immune system
fuzzy neural nets
Opis:
The article concerns the analysis of classification of medical data by use of selected method of artificial intelligence: case-based reasoning. The subject of the research is the assessment of effective treatment, being one of the most important medical problems. The basis work of the assessment system should be one of the classification methods. The aim of the attempted research is to study which of the enumerated method will be able to group data containing incomplete information in the best way. The classified data are descended from the patients with nephroblastoma and patients with backbone pain. The final aim of the research is to work out the functioning method of the learning system, assisting the doctor with making a decision during working out on patient's treatment therapy, and making analyses of the treatment effectiveness. On the basis of the medical tests, the system will classify the data assigning them to the appropriate therapy groups. Moreover, in the system will be used artificial immunology as the method of generalizing or extrapolating of the gathering and considering so far cases.
Źródło:
Journal of Medical Informatics & Technologies; 2007, 11; 221-226
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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