Just as any other professions, medicine has its own "language". The words or terms which make up the language of medicine are referred to as "Medical Terminology". The majority of medical terms are based in Latin or Greek This course aims to provide basic concepts on medical terms used during daily medical practice.

This course aims to provide a general overview of preclinical basic sciences including those are dealing with normal body functions, disordered body functions, causes of diseases and drug treatment. The examples of these disciplines are anatomy, physiology, biophysics, histology and embryology, biochemistry, pathology, microbiology, pharmacology, and genetics.

This course provides an overview of diagnostic and treatment modalities in medical and surgical clinical sciences which include medicine, surgery, gynecology and obstetrics, pediatrics, radiology and dermatology.

After having this course the students will be familiar about basic concepts of medical informatics which covers data processing in health care, examines the integration of medical applications and communication technology and telemedicine.

After having this course the students will be informed about current systems on health records. The topics cover data entry, minimum data sets, standarts in health records, medical coding and classification systems.

Having this course the students will be familiar with basic information concepts used in clinical sciences and consequently be able to analyze the needs and provide solutions.

After having this course the students will be knowledgeable about tools for decision support and their application to patient management by means of practical examples. The discussion topics include measurement of uncertainty, probability in medicine, differential diagnosis, sampling information, assessment of quality of medical data, selection and evaluation of diagnostic tests, decision making and cost/benefit analysis.

Classification of Biomedical Signals , Origin of Biosignals and their systemic properties (Nerve action potential and ENG, myoelectric activity and EMG, myocardiac activity and ECG, brain activities and EEG), Memory and Correlation Analysis in Biomedical Signals, Application of essential techniques on biomedical case studies, Noise sources in biomedical systems, Examples of noise removal and signal compensation, Modeling biomedical system based stochastic signals, Preprocessing and feature extraction.

The concept of knowledge, prepositional and predicate calculus in classical logic, knowledge representation, inference, clausal and conjunctive normal form. Resolution refutation, forward chaining (data driven ) and backward chaining (goal driven) in implicative form for deducing a particular conclusion. Uncertainty in the base of probability, certainty factor. Fuzzy logic. Popular (AI) artificial intelligence languages. Structure of expert systems and applications in CAD (computer aided design). Real time applications of KBS (knowledge based systems).

Basic concepts of image reconstruction algorithms. Algorithms for reconstruction with nondiffracting sources. Measurement of projection data - the nondiffracting case. Aliasing artifacts and noise in computerized tomography images. Tomographic imaging with diffracting sources. Algebraic reconstruction algorithms (ART, SIRT, SART). Reflection tomography. X-Ray Tomography, Emission Computed Tomography, Ultrasonic Computed Tomography, Magnetic Resonance Imaging, Electrical Impedance Tomography.

Knowledge representation and learning paradigms. Adaptation and generalization in neural networks. The structure of common neural network unit in comparison with the biological neuron. Perceptron and multilayer perceptrons. Types of backpropagation learning algorithms and their fundamental principles. Fuzzy control of backpropagation learning. Radial Basis Function (RBF) networks and their learning strategies. Temporal processing: temporal backpropagation and recurrent networks. Unsupervised networks and their learning rules. Application of neural networks in medicine especially in ECG signal processing.

Fundamentals of digital image. Image transformations: FFT, DCT, etc. Image enhancement: histogram modification, image smoothing and sharpening. Image restoration. Coding. Segmentation. Representation and description.

Fundamental concepts of pattern recognition, pattern classes, pattern features, extraction of features, classification. Statistical decision theory, linear decision functions, Bayes classifier. Supervised learning, estimation of probability density functions, maximum likelihood estimation. Nonparametric pattern recognition techniques, nearest neighbor and k-nearest neighborhood algorithms, least squares algorithm. Unsupervised learning, clustering, estimation features with orthogonal functions. Syntactic pattern recognition.

Quantitative methods in engineering and physical science to problems in biology and medicine, biological systems to foster insights into the design and development of artificial substitutes, biomechanics including solids and fluids, biotransport in the lung and circulatory system, stimulation response in sensory systems, biomaterials of surgical implants, biocontrol, and bioinstrumentation.

Definition and content of biotechnology, life chemicals, enzyme kinetics and action mechanisms, factors affecting enzyme activity, enzyme immobilization techniques, production and purification of enzymes, usage and medical applications of free and immobilized enzymes, introduction to microbiology, batch and continuous fermentation processes; some medical applications.

Frequency distribution and descriptive statistics for frequency distributions. Tables and graphics. Significance tests. Simple lineer regression and correlation.

Introduction to economics and basic concepts; basic problems in economics; introduction health economics and basic concepts and contents; value of health; factors affecting health status and economic development, equity issues; characteristics of health care demand and supply, nature of the health care market, role of government; resource use in health sector and health financing issues and examples; health systems and examples, Turkish health system; economic analysis techniques; pharmacoeconomics and other practice fields.

The student is expected to make a presentation in front of a juri about a research topic, he has chosen in agreement with his supervisor.

One-term project. The result will be presented as a report.