Program tanımları
Objectives
Health sciences and medicine are one of the prominent application areas of information and technology. Measurement and imaging methods, testing, analysis and patient monitoring instruments are developing and increasing in numbers at a very fast pace. As a result, health information is getting richer and information collected from patients is increasing at a very fast rate. The importance of information technologies in adopting the research results into practice is indispensable, under the circumstances of the expanding pace of research conducted in medicine.
The purpose of Medical Informatics is the forming, shaping and sharing of this information, and providing methodologies in the diagnosis and treatment of patients.
The analysis and synthesis of advancements made in all areas of science have always been in the agenda of Medical Informatics.
This priority will necessarily continue to persist in importance for the interdisciplinary unifying approaches. When this necessity is considered, the biggest step that Turkey should take in Medical Informatics is to start raising specialists in this field. It is necessary to establish shared and reusable processes, and to carry these processes into inter-institutional dimension in providing health services using the advantages of information technologies.
The objectives of the Medical Informatics graduate programs are:
* to provide the specialists, researchers working in all health sectors with knowledge and experience they need in carrying out their work more effectively using the information systems and methodologies.
* to raise academicians / researchers, to make inter-disciplinary scientific research, and to bring together the researchers from both disciplines in Medical Informatics field.
Career Opportunities
Health and Medical Informatics have a very broad and diverse position advantage. Both public and private sectors are in immediate need of graduates of this program. Some examples are information technology companies developing/supporting software, the IT-management and quality management departments of all hospitals and health providers, clinical managers, health insurance firms, nursing services management, city health offices and many other health organizations. In addition, various projects supported by international financial firms need specialists of this field. Government based Social Security institutions are also potential employers of such specialists.
Program Structure
Degree Requirements
M.Sc. Degree Requirements - Thesis Option
* 3 (3-credit) core course - 9 credits total
* 5 (3-credit) elective course - 15 credits total
* 1 (non-credit) seminar course
* Master's Thesis (non-credit)
M.Sc. Degree Requirements - Non-Thesis Option
* 3 (3-credit) core course - 9 credits total
* 7 (3-credit) elective course - 21 credits total
* 1 (non-credit) seminar course)
* Term Project (non-credit)
Graduate Curriculum
Deficiency Courses
Accepted students must complete their scientific background requirements before starting the program.
For Students Coming From a Non-Health Field
(Taken from Sağlık Bilimleri Enstitüsü, Hacettepe Üniversitesi)
BIS 535/735 Biyoistatistik
TEB 510 Medical Terminology
TEB 502 Introduction to Basic Medical Sciences (or TEB 503 Introduction To Clinical Medical Sciences)
For Students Coming From Health and Medicine Field
BIS 535/735 Biyoistatistik (taken from Sağlık Bilimleri Enstitüsü, Hacettepe Üniversitesi)
MAT 157 Basic Calculus I
Specialization Areas in the program*
1. HIS and Clinical Informatics
2. Medical Image/Signal Analysis
3. Medical Decision Support
4. Neuroscience
*By the end of the first year, all students have to choose one of the 4 specialization areas above.
Core Courses
BİS 610 Karar Verme Sürecinde İstatistiksel Yöntemler
Description: Temel olasılıksal kavramlar; Tanı testlerinin performansını değerlendirmek için kullanılan ölçüler; Paralel ve seri test uygulamaları ve birleşik test performans ölçüleri; Karar doğruluğunun saptanması; ROC analizi; Tanı testlerinin değerlendirilmesinde Bilgi kuramı yaklaşımı; Optimum pozitiflik kriterlerinin (eşik değerlerinin) belirlenmesi; Yarar-maliyet dengesi açısından uygun test ya da test kombinasyonu seçimi.
IS 545 Object Oriented Programming and Data Structures
The basic Object Oriented Principles will be discussed using a modern programming language i.e. Java. The theory will be used in practice to implement Data Structures which is very important in algorithm development.
The core of the class will depend on using object oriented principles to implement algorithms in Data Structures using Java. Altough some reading is required, practice is more important in learning any programming language.
MIN 502 Introduction to Medical Informatics
Description: This course presents an overview of medical informatics and its main applications. Primary topics include: Reasons for necessity of systematically processing data, information and knowledge in medicine and health care, benefits and current constraints of using information and communication technology in medicine and health care, medical informatics as a discipline, medical data and records, coding classification, database and reference models, interfaces, data acquisition, processing and exchange standards, medical knowledge, decision and diagnostic support, medical information systems, administrative, clinical and ancillary information systems, implementations and evaluations, telemedicine and internet applications, efficient and responsible use of information processing tools to support health care professionals practice and their decision making.
HAS 640 Epidemiyolojinin Temel Ilke ve Yöntemleri
Description: Saglik sorunlarini belirlemek, neden sonuç iliskilerini ortaya çikarmak, çözüm önerileri üretebilmek için çesitli bilgilerin verilmesi ve kisa süreli bir arastirma uygulanmasi.
HAS 645 Epidemiyolojide Arastirma Programlama ve Uygulama
Description: Description: Arastirma yöntemleri uygulatmak, beceri kazandirmak amaciyla seçilen bir konuda tüm asamalari ile birlikte bir arastirmanin yapilarakrapor haline getirilmesi.
BIS 656 Istatistiksel Hesaplama
Description: Non Credit.
BIS 736 Saglik Bilimlerinde Arastirma Yöntemleri
Description: Arastirmada hata kaynaklari, arastirmanin planlanmasi, örnekleme.Arastirma türleri. Veri dizgileme, verinin analizi ve yorumu, rapor yazimi.
ES 503 Finite Element Method
Description: Introduction to calculus of variations, weighted residuals method. Properties of finite elements. Ritz and Galerkin methods. Applications in bondary value problems. Two dimensional and time dependent problems.
EE 430 Digital Signal Processing
Description: Discrete-time signals and systems. Discrete Fourier transform. Sampling and reconstruction. Linear time-invariant systems. Structures for discrete-time systems. Filter design techniques. Fast Fourier Transform methods. Fourier analysis of signals using discrete Fourier transform. Optimal filtering and linear prediction. (Prerequisite: EE 301)
EE 543 Neurocomputers
Description: FROM BIOLOGICAL NEURON TO ARTIFICIAL NEURAL NETWORKS, RECURRENT NEURAL NETWORKS, NEURAL NETWORKS AS ASSOCIATIVE MEMORY, COMBINATORIAL OPTIMIZATION BY NEURAL NETWORKS, ANNEALING BY STOCHASTIC NEURAL NETWORK FOR OPTIMIZATION, LEARNING IN FEEDFORWARD NETWORKS, RECURRENT BACKPROPAGATION, DATA CLUSTERING AND SELF ORGANIZING FEATURE MAPS, RADIAL BASIS FUNCTION NETWORKS.
EE 553 Optimization
Description: Mathematical preliminaries on functions of several variables. Convexity and convex functions. Unconstrained minimization problems. Computational algorithms such as steepest descent, Newton and quasi-Newton methods. Constrained minimization problems and Kuhn-Tucker theory. Fundamental theorems of linear optimization and the simplexs algorithm.
EE 642 Introduction to Mathematical Bases of Computer Graphics
Description: Two Dimensional Transformations of Points and Lines, Three-Dimensional Transformations, Plane Curves, Space Curves, Surface Description and Generation.
CENG 538 Advanced Graphics and User Interfaces
Description: This course covers advanced illumination and rendering algorithms, their accelaration techniques and massively multiplayer online game (MMOG) architectures. The topics include: ray tracing, radiosity, parallel global illumination on multiprocessors, space subdivision, multiresolution modelling, GPU programming and game development frameworks.
CENG 555 Object Oriented Database Systems
Description: Introduction to object-oriented database systems. The object-oriented database systems manifesto. Exodus storage manager. ORION object-oriented DBMS. O2 object-oriented DBMS. R trees, R+ trees and R* trees. Implementation issues for object-oriented database systems.
CENG 559 Data Security and Protection
Credit: 3
Description: Symmetric ciphers: Classical and modern. The Data Encryption Standard(DES), authentication, key management, asymmetric (public key) ciphers, digital signatures.
CENG 561 Artificial Intelligence
Credit: 3
Description: Problem solving and search strategies. Game playing. Knowledge Representation. Expert systems and rule chaining. Vision. Natural language processing. Machine translation. Machine learning. Neural networks.
CENG 562 Machine Learning
Description: Paradigms of machine learning, inductive deductive abductive forms of learning, cognitive aspects of learning, connectionless models of learning, programming environments for learning programs.
CENG 564 Pattern Recognition
Description: An introduction to the machine recognition of one, two or higher dimensional patterns. Statistical and linguistic approaches. Survey of application areas. Bayes Decision Theory, decision bounderies, classifiers and discriminant functions. Estimation of parameters. Clustering. Feature selection. Structural approaches to PR. Neural network recognizers. Applications.
CENG 568 Knowledge Engineering
Description: Basic concepts and techniques. Knowledge representation. Drawing inferences. Tools and languages for expert systems. Knowledge engineering and expert systems development. Knowledge equization. Current expert system applications.
CENG 569 Neurocomputing
Description: Learning and generalization. The basic perceptron and linear separability. Multi-layer perceptrons and the backpropagation algorithm. The Hopfield Model and its dynamics. Bi-directional associative memory. Recurrent Networks. Unsupervised Learning and self organizing maps. The counter propagation network. Boltzman Machine and Simulated Annealing. Recent advances.
CENG 571 Numerical Analysis - I
Description: Accuracy in Numerical Analysis. Survey and critical comparison of numerical methods for matrix inversion. Systems of linear algebraic equations and eigenvalue problems. Systems of non-linear equations. One and two dimensional interpolation and numerical approximation. Numerical differentiation and integration. Selected algorithms will be programmed for solution on computer. The complexity of algorithms. Lower and upper bound theory. Design of the following algorithms: Divide-and-Conquer, the greedy approach, dynamic programming, backtracking, branch-and-bound. NP-Complete and NP-Hard problems.
CENG 574 Statistical Data Analysis
Description: Multivariate statistical analysis with applications especially in the field of Computer Engineering. Review of introductory concepts in statistics. Hypothesis testing. Regression analysis. Discriminant analysis. Principle component analysis. Factor analysis. Applications with the use of existing computer packages.
CENG 576 Numerical Methods in Optimization
Credit: 3
Description: Types of optimization problems in a variety of fields; efficiency of common methods of solution. Definition of optimization, extrema of functions of n variables, linear programming and the simplex method, nonlinear programming and application of common methods to optimization problems.
CENG 580 Distributed Artificial Intelligence
Description: Concurrency and distribution in AI. Agents: micro and macro views.Rational agency: economic/game theoretic, logical. BDIarchitecture. Multi-agent real-time search. Multi-agent learning. Reinforcement learning. Opponent modeling. Coordination: cooperation, competition, communication and conflict resolution among agents.
CENG 581 Automated Reasoning
Description: Geometric reasoning, temporal reasoning, uncertain reasoning, non-monotonic reasoning, induction, metaknowledge and metareasoning, state and change, planning, intelligent agent.
CENG 583 Computer Vision
Description: Edge detection and contour extraction. Region segmentation. Perspective projection and camera calibration. Matching and stereo. Projective geometry. Three dimensional reconstruction. Dynamic scene analysis.
Introduction to Information Systems
Description: The course introduces the students to the fundamental concepts of information systems. These include: systems theory; management information; conceptual models of information in organizations; MIS; decision support systems; enterprise resource planning systems; information systems planning; organizing for information system projects; IS project lifecycle models; IS development and maintenance principles; organization, management and control of IS; IS outsourcing.
IS 502 Information Systems Group Project
Description: This course aims to give students professional experience in information systems development. Student teams work on the specification, design, implementation and acceptance testing phases of different information systems projects. Each team works on a different phase of a different project and produces professional quality documentation. The documentation is distributed among all teams, who then collectively participate in formal review sessions held in class for each phase of each project. Project topics may be selected from diverse areas such as engineering, business management, provided that the project plan is realistic and the estimated duration fits a semester.
IS 503 Database Management Applications
Description: Data abstraction/independence, data models (Entity-Relationship model, Object Oriented model, relational/network/hierarchical model), database languages (DDL, DML), database administrator/user. Storage and File Structures. indexing and hashing. Relational Model: formal query languages (Relational algebra, Relational calculus), commercial query languages (SQL). Relational database design: integrity constraints, data dependencies, normal forms. Transaction processing and concurrency control.
IS 504 Computer Networking Applications for Information Systems
Description: Layered network architectures and standard layer functions. ALOHA, Ethernet and Token Ring networks. Framing and error control. Routing and switching. Internetworking. TCP/IP. The Internet. Application support protocols. Network security.
IS 507 Introduction to Software Engineering
Credit: 3
Web Site: http://www.ii.metu.edu.tr/~is507
Description: The course introduces the fundamentals of software management and software system models with an emphasis on software development process models, project management techniques and contemporary modeling notations.
IS 551 Computer Security and Cryptography
Description: Introduction to privacy, data security, communication security and file security in computers and computers networks. Introduction to cryptography, its role in electronic data processing. Block ciphers, stream ciphers and DES, data encryption standard. Trusted computer systems, issues in authentication and verification.
IS 564 Design, Development and Evaluation of Instructional Software
Description: Overview of Computer Aided Instruction (CAI): Types, strengths, and weaknesses, effective CAI. Implications of the learning for the courseware design and authering. Features, advantages and limitations of different CAI modes. Planning and managing CAI projects. Desinging and producing CAI. Evaluation and revision. Computer managed instruction. Computerized testing.
IS 566 Image Processing Algorithms
Description: Introduction, Transform Techniques, Enhancement, Edge Detection, Morphological Image Processing, Color Image Processing, Segmentation, Image Representation and Compression. The course will be offered through Internet.
IS 781 Knowledge Representation and Data Mining
Description: The course introduces principles and techniques of data mining and knowledge discovery. It emphasizes the advantages and disadvantages of using these methods in real world systems and provides hands-on experience. Its technical focus is on qualitative and quantitative knowledge based systems and learning systems. Topics include key issues of data mining and machine learning, decision trees, artificial neural networks, Bayesian learning, instance based learning, expert systems, fuzzy systems, and genetic algorithms.
MIN 503 Electronic Health Records and Coding
Description: This course gives an overview of contemporary health records and then introduces computer based patient records/electric health records. Topics include data entry, minimum data sets, general applications of electronic health records, standards in health and medical informatics, importance of coding and standardization, clinical uses of CPR. Current applications in all areas of medicine; like use of CPR in primary care to specialized clinical/departmental information systems and HIS applications shall be given. Reasons for necessity of medical coding and classification will be described. Primary topics include history of classification, important classification systems like ICD, SNOMED, MESH, ICPC, CPT, and practical application and uses of these coding systems.
MIN 524 Medical Imaging Technology (currently IS 574)
Description: The course provides a basic overview of the fundamental medical imaging technologies at an introductory level for graduate students of any background. Physical principles, data acquisition techniques and mathematical formulation of imaging problems are briefly introduced. Digital medical image processing/analysis techniques, as well as telemedicine/teleradiology concepts (including digital image communication in medicine-DICOM) are also covered.
MIN 701 Networking for Health Information Systems and Telehealth
Description: The course summarizes the fundamentals of computer networking from a health informatics perspective and introduces the students to the underlying concepts of telehealth. Topics on computer networking include hardware and software components, protocol layers, application layer protocols, socket programming, Internet protocol, multimedia networking and local area networks. The subjects on telehealth are discussed starting by describing history, definitions and current applications. Then, the advantages and barriers for successful telehealth projects are emphasized, types of telehealth projects are discussed, and security and legal issues are given. More advanced topics such as virtual reality are also presented.
Name: MIN 702 Evaluation Methods in Health Informatics
Description: Medical Informatics is a multifaceted interdisciplinary field. In this area clearly there is a need for good research design, carry out, analysis, evaluation and interpretation of wide range quantitative and qualitative techniques. This course will be useful for all medical informatics professionals.
Name: MIN 703 Medical Imaging Applications
Description: This course provides a basic overview of the applications of medical imaging and Radiology Information Systems (RIS). Practical applications of X-ray radiography, computed tomography, magnetic resonance imaging, ultrasound and ultrasonography, Doppler ultrasound and Doppler ultrasonography, computed radiology, digital radiology, radiology information systems and other medical imaging techniques are briefly introduced. Various image processing applications on medical images are introduced in both clinical and technical perspectives.
MIN 704 Reasoning under uncertainty
Description: Uncertainty models and information representations: types of uncertainty (predictive, retrodictive, diagnostic, prescriptive) and uncertainty measures (incompleteness, imprecision, vagueness, inconsistency, dissonance, confusion, etc.). Entropy and set-theoretic reprentation of information (crisp sets, fuzzy measures like Belief functions and fuzzy sets). Minimization of uncertainty. Decision making under uncertainty. Applications to medical informatics.
MIN 705 Neuroimaging: Anatomy, Physiology and Function of the Human Brain
Description: The course introduces all three aspects - anatomy, physiology and function- of neuroimaging, which is enlisted as a sub-field of neuroinformatics. Theoretical knowledge on neuroanatomy and function of the brain will be complemented by hands-on applications with the existing online data analysis packages. The anatomy of the brain will be studied over MR images using volumetric and shape based techniques. The physiology of the brain will be studied over cytoarchitecture. The function of the brain will be studied over pet-spect, meg, eeg, and fMRI, with more emphasis on fMRI.
IAM 501 Introduction to Cryptography
Credit: 3
Description: Historical Introduction to Cryptography: General Principles, Monographic-Polygraphic Systems, Monoalphabetic-Polyalphabetic Systems, Substitution Ciphers, Transposition Ciphers, Frequency Analysis, Kasiski Analysis. Shannonss Theory: Perfect Secrecy, Entropy. Cryptographic Evaluation Criteria and Cryptanalysis. Public and Private Key Cryptography. Block Ciphers: Diffusion, Confusion, Feistel Structure. Stream Ciphers: Shift Registers, Synchronous and Self-synchronous Ciphers, Linear Complexity. Public Key Cryptography: Fundamental Concepts, NP-Hard Problems, Discrete Logarithm, Factorization, Subset Sum, RSA, Diffie Hellman Key Exchange Protocol, DSA, Cryptographic Protocols
Type: Technical
IAM 564 Basic Algorithms and Programming
Description: Basic programming, introducing MATLAB, programming with MATLAB, basic algorithms and problem solving in Linear Algebra, Differential Equations, Optimization and so on. Introducing LATEX.
Type: Technical
