Polish MKIB2S22004M

Intelligence. Artificial Intelligence (AI). Turing Test. Methods of knowledge representation in Al. characteristic biomedical data. The organization and operation of the expert system. concept heuristics. Search heuristics and classic. Decision trees. Inference. Models learning and artificial neural networks. Model classification, characteristics and areas of decision-making. Neural classifier. Error back propagation method and its modifications. Cluster analysis. Genetic algorithms. Examples of medical applications.

(in Polish) Rodzaj przedmiotu

(in Polish) Obowiązkowy

(in Polish) Tryb prowadzenia

(in Polish) Lektura monograficzna

Course coordinators

Jolanta Pauk

Learning outcomes

Student: lists and describes the main methods of artificial
intelligence Intelligent; quotes and tells how to search thesolutions; can classify biomedical data; can learn how to design and artificial neural network; evaluate machine intelligence.

Assessment criteria

Lecture - 2 tests, project - assessment reports.

Bibliography

1. Red. Duch W. iin.: Biocybernetylo i inżynieria biomedyczna 2000, Tom 6 - Sieci neuronowe. Akademicka Oficyna Wydawnicza Exit, Warszawa 2000.
2. FiasińskiM.: Wstęp do sztucznej inteligencji: Wydaw. Naukowe PWN, Warszawa 2011.
3. Red. Nałęcz M.: Biocybernetyka i inżynieria biomedyczna 2000, Tom 7 - Systemy komputerowe i teleinformatyczne w służbie zdrowia. Akademicka Oficyna Wydawnicza Exit, Warszawa 2002.
4. Rutkowski L. Metody i techniki sztucznej inteligencji. Wydaw. Naukowe PWN, WarsawP