Information Package
baskent.edu.tr

Program of Computer Engineering (English)

CSE473

MEDICAL INFORMATICS

Course Code
CSE473
Semester
-
Theory+Practice
3 + 0
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Learn medical information flow
  2. Learn medical business processes
  3. Learn standards associated with medical information systems
  4. Learn ethics, privacy and security issues in medical informatics.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course DescriptionPatient data. Electronic medical records. Coding standards. Clinical information systems. Hospital management informations systems. Medical decision support systems. Medical imaging technologies. Telemedicine. Ethics, privacy and security issues in medical informatics. Introduction to data mining for medical informatics
Course Contents
WEEK TOPICS
1st Week Introduction to medical informatics
2nd Week Patient data, Electronic medical records
3rd Week Bioinforamtics
4th Week Clinical information systems, Hospital management informations systems.
5th Week Medical decision support systems
6th Week Medical imaging technologies, Telemedicine
7th Week Ethics, privacy and security issues in medical informatics
8th Week Mid-term
9th Week Introduction to data mining for medical informatics
10th Week Machine learning for medical informatics
11th Week Machine learning for medical informatics
12th Week Machine learning for medical informatics
13th Week Machine learning for medical informatics
14th Week Current trends in medical informatics
15th Week General Review
Recommended or Required Reading1.Handbook of Medical Informatics, 1997, 1.ed., Bemmen, Musel and Musel
2.Health Informatics: Practical Guide, Seventh Edition, William R. Hersh and Robert E. Hoyt
3.Biomedical Informatics : Computer Applications in Health Care and Biomedicine, 4th Edition, Edward H. Shortliffe, James J. Cimino.
4.Machine Learning for Healthcare Applications, 1st Edition, Sachi Nandan Mohanty, G. Nalinipriya, Om Prakash Jena, Achyuth Sarkar
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Experiment
  • Problem Solving
  • Practice
  • Project
  • Report Preparation
  • Presentation
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Assignment 4 15
Project 1 15
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4
K1
K2
K3 X X X X
K4
K5
K6
K7
K8
K9 X X
K10
K11 X X X X