Intelligent Systems Research Group
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of human expert systems are designed to solve complex problems by reasoning about knowledge, represented mainly as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software.
For more than last ten years, Artificial Neural Networks (ANN) have received a great deal of attention and they have being touted as one of the greatest computational tools ever developed. ANNs simulate learning and generalization behavior of the human brain through data modeling and pattern recognition for complex multidimensional problems. Just as the brain is composed of numerous neurons, a neural network has similar structure, artificial neurons. Through data modeling and pattern recognition, these structures simulate learning and human brain behavior. There is a significant difference between an ANN model and a statistical model. ANN can generalize the relationship between independent and dependent variables without a specific mathematical function.
Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO.
The aim of this research group is to develop various Expert Systems based on Artificial Neural Networks and Fuzzy Logic. For achieving this goal, techniques, and protocols for acquiring biological data are to me examined. Also, this research group will focus on developing telemetry systems. Telemedicine and telemetry can help diagnosis of various diseases in remote areas, by supporting for example local non-specialized healthcare services (e.g. family doctors) with the remote transmission of locally acquired data to reference centers, where specialized doctors can tele-diagnose the disease.
Teaching Assistant Lejla Gurbeta, PhD candidate
Berina Alić, Master student
Dijana Sejdinović, Master student
Ahmed Osmanović, Master Student
Sabina Halilović, Master student
Halilovic S, Avdihodžić H, Gurbeta L: Micro cell culture analog Apparatus (µCCA) output prediction using Artificial Neural Network, 5th Mediterranean Conference on Embedded Computing (IEEE MECO 2016), Bar, Montenegro, 2016
Badnjević A, Gurbeta L, Cifrek M, Marjanović D: Diagnostic of Asthma Using Fuzzy Rules Implemented in Accordance with International Guidelines and Physicians Experience, 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (IEEE MIPRO), At Opatija, Croatia, 2016
Badnjević A, Gurbeta L, Cifrek M, Marjanović D: Classification of Asthma Using Artificial Neural Network, 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (IEEE MIPRO), At Opatija, Croatia, 2016
Alić B, Sejdinović D, Gurbeta L, Badnjević A: Classification of Stress Recognition using Artificial Neural Network, 5th Mediterranean Conference on Embedded Computing (IEEE MECO 2016), Bar, Montenegro, 2016
Aljović A., Badnjević A., Gurbeta L.: Artificial Neural Networks in the Discrimination of Alzheimer's disease Using Biomarkers Data, 5th Mediterranean Conference on Embedded Computing (IEEE MECO 2016), Bar, Montenegro, 2016
Badnjevic A., Cifrek M., Koruga D., “Classification of Chronic Obstructive Pulmonary Disease (COPD) using integrated software suite”, IFMBE XIII Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON), 25-28. September 2013., Sevilla, Spain.
Badnjevic A, Cifrek M, Koruga D, Osmankovic D. „Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease“ BMC Medical Informatics and Decision Making Journal, 2015, 15(Suppl 3):S1; doi: 10.1186/1472-6947-15-S2-S1
B.Sc. THESIS SUPERVISION
Project name - Classification of metabolic syndrome patients using implemented expert system, Berina Alić, June 2016
Project name - Classification of prediabetes and type 2 diabetes using artificial neural network , Dijana Sejdinović, September 2016;
Application of Artificial Neural Network in modeling of photo-degradation suspension of manganese-doped zinc oxide nanoparticles under visible-light irradiation,
Artificial Neural Network: Gas recognition
Artificial Neural Network: Machine-Learning Tool in Breast Cancer Classification