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Why Automatic Understanding?

Ryszard Tadeusiewicz, Marek R. Ogiela

University of Mining and Metallurgy

Cracow, Poland

 

Typical applications of Artificial Intelligence (AI) methods in biomedicine (e.g. medical diagnostics), in the area of engineering problems (e.g. control systems) and also in intelligent economical information systems includes some traditional techniques: intelligent data processing and analysis, pattern recognition, neural networks, genetic algorithms and expert systems. Data processing and analysis give us better description of the objects or processes under consideration. Pattern recognition give us possibilities of its classification – for example in case of automatic diagnostics. Neural network helps us to build behavioral models for control or forecasting. Genetic algorithms can solve optimization problems. Expert systems can advise us, what we ought to do in particular situations. This short outlook presents general view over the typical AI landscape.

In many biomedical, economical, and engineering problems it is enough. If we can solve presented problems and if we can build AI tools for intelligent data analysis, recognition and modeling – we are happy. This is true, but definitely not in all situations. Sometimes solving of complex problems leads to the necessity of understanding some signals, patterns and situations instead of simple processing, classification and interpretation. In fact understanding of the problem is first necessary step for intelligent solving of the problem, when we use natural (not artificial) intelligence. Understanding of the problem is not special case of signal processing – it needs also some knowledge and demands special type of data processing. Details of natural understanding are very complicated and obscure, therefore we can talking about understanding in terms of psychology and in frames of cognitive science, although in fact we can not understood the natural understanding process!

Nevertheless we can propose effective methods of artificial imitation of understanding. Although it sounds strange - in fact it is definitely possible to build up the system for automatic understanding of selected data, signals and situations. This fact was proven by the authors in many previous papers and books on the base of many examples of medical images. If computer powered by special AI programs can understood the nature of disease on the base of analysis of features of some medical images it can be applied also to the solving of other complex problems, demanding automatic understanding as a part of its automatic solving. In the paper we describe the general methodology of the automatic understanding and we show how to use this methodology for solving selected biomedical, economical and also engineering problems.

 

Professor Ryszard Tadeusiewicz studied at the Electrical Engineering Department of the University of Mining and Metallurgy in Krakow from which he graduated (with honors) in 1971. Additionally, after receiving his degree in Automatic Control Engineering, he studied at the Faculty of Medicine at the Medical Academy in Krakow, as well as undertook studies in the field of mathematical and computer methods in economics. Since April 1971 he has done research in the areas of bio-cybernetics, automatic control engineering, and computer science. In 1975 he was awarded the Ph.D. degree, and in 1981 the degree of Doctor of Sciences (habilitation). In 1986 he became Professor and in 1991 the Full Professor at the University of Mining and Metallurgy. He obtained 9 Honorary Doctor awards from Polish and foreign Universities.
He has written and published over 500 scientific papers, which were published in prestigious Polish and foreign scientific journals as well as numerous conference presentations - both national and international. Prof. Tadeusiewicz also wrote over 70 scientific monographs and books, among them are highly popular textbooks (which had many reprints). He was supervisor of 44 doctoral thesis and reviewer of more than 200 doctoral thesis. In 2003 all Polish scientists elected him to be the Member of Central Committee for Scientific Degrees and Scientific Titles (organ by Prime Minister of Polish Government).
In 1996, in universal and secret elections he was elected the Vice-Rector for Science of the University of Mining and Metallurgy, and in January 1998 its Rector. He was re-elected 1999 for the term 1999 - 2002 and again 2002 for the term 2002-2005. In February 1998 Prof.Tadeusiewicz was elected the Corresponding Member of Polish Academy of Sciences and Arts (PAU), in February 2000 he become Foreigner Member of Russian Academy of Natural Sciences, in May 2002 he was elected for the grade Corresponding Member of Polish Academy of Sciences (PAN), and in September 2005 he become fellow World Academy of Art and Science (San Francisco).

Further information can be found at: http://www.agh.edu.pl/english/tad/


Professor Marek R. Ogiela works in Bio-Cybernetics laboratory at the AGH University of Science and Technology in Krakow. In 1992 graduated from the Mathematics and Physics Department at the Jagiellonian University. In 1996 for his honours doctoral thesis on syntactic methods of analysis and image recognition he was awarded the title of Doctor of Control Engineering and Robotics at the Faculty of Electrical, Automatic Control, Computer Science and Electronic Engineering of the AGH University of Science and Technology. In 2001 he was awarded the title of Doctor Habilitated in Computer Science for his research on medical image automatic analysis and understanding. In 2005 he received a professor title in technical sciences. Member of numerous world scientific associations as well as of the Forecast Committee `Poland 2000 Plus´ of the Polish Academy of Science and member of Interdisciplinary Scientific Committee of the Polish Academy of Arts and Sciences (Bio cybernetics and Biomedical Engineering Section). Author of more than 90 scientific international publications on pattern recognition and image understanding, artificial intelligence, IT systems and biocybernetics. Author of recognised monographs in the field of cryptography and IT techniques; author of an innovative approach to cognitive medical image analysis. For his achievements in these fields he was awarded many prestigious scientific honours, including Prof. Takliński´s award (twice) and the first winner of Prof. Engel`s award, nominated in the category Science to the Silver Nike award in 2003. Reviewer of world scientific periodicals, including: IEEE Transactions on Systems, Man, and Cybernetics, Artificial Intelligence in Medicine Journal and Journal of Intelligent & Robotic Systems. Currently employed by AGH at the post of Automatics where he conducts vast scientific research on Medical Imaging and information encrypting.

Further information can be found at: http://home.agh.edu.pl/~mogiela/index_en.html

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