MD3403 MEDICAL EXPERT SYSTEMS SYLLABUS | ANNA UNIVERSITY BE MEDICAL ELECTRONICS ENGINEERING 7TH SEM SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY SEVENTH SEMESTER BE MEDICAL ELECTRONICS ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI,TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MD3403 MEDICAL EXPERT SYSTEMS L T P C
3 0 0 3
UNIT I INTRODUCTION TO AI 9
Definition of AI – importance of AI – problem solving, searching, heuristic searching.
UNIT II KNOWLEDGE REPRESENTATION 9
Preposition Logic – Clause form – Predicate logic – Resolution – Inference Rules –
Unification – Semantic networks – frames – conceptual dependency – Scripts –
knowledge representation using rules – rule based systems.
UNIT III EXPERT SYSTEMS 9
Expert system architecture - non-production systems architecture– knowledge
acquisition and validation - Knowledge system building tools
UNIT IV LEARNING & DECISION MAKING 9
Types of learning – general learning model – learning by induction – generalization &
specialization – inductive bios – explanation based learning
UNIT V CASE STUDY 9
Study of medical expert systems – MYCIN, EMYCIN - development of medical expert
systems – sample Case studies
TOTAL: 45 PERIODS
REFERENCES:
1. Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”,
Prentice Hall of India, Delhi, 2001.
2. Watterman. “Expert Systems”, Mc-Graw Hill, New York, 1991
3. George F Luger, “Artificial Intelligence, structures and strategies for complex problem
solving”, Pearson Education Delhi, 2001.
4. Elain Rich and Kevin Knight, “Artificial Intelligence”, 2nd edition, Tata McGraw Hill,
1993.
5. R.D.Lele, “Computers in Medicine,” Tata McGraw Hill, NewDelhi-1989.
MD3403 MEDICAL EXPERT SYSTEMS L T P C
3 0 0 3
UNIT I INTRODUCTION TO AI 9
Definition of AI – importance of AI – problem solving, searching, heuristic searching.
UNIT II KNOWLEDGE REPRESENTATION 9
Preposition Logic – Clause form – Predicate logic – Resolution – Inference Rules –
Unification – Semantic networks – frames – conceptual dependency – Scripts –
knowledge representation using rules – rule based systems.
UNIT III EXPERT SYSTEMS 9
Expert system architecture - non-production systems architecture– knowledge
acquisition and validation - Knowledge system building tools
UNIT IV LEARNING & DECISION MAKING 9
Types of learning – general learning model – learning by induction – generalization &
specialization – inductive bios – explanation based learning
UNIT V CASE STUDY 9
Study of medical expert systems – MYCIN, EMYCIN - development of medical expert
systems – sample Case studies
TOTAL: 45 PERIODS
REFERENCES:
1. Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”,
Prentice Hall of India, Delhi, 2001.
2. Watterman. “Expert Systems”, Mc-Graw Hill, New York, 1991
3. George F Luger, “Artificial Intelligence, structures and strategies for complex problem
solving”, Pearson Education Delhi, 2001.
4. Elain Rich and Kevin Knight, “Artificial Intelligence”, 2nd edition, Tata McGraw Hill,
1993.
5. R.D.Lele, “Computers in Medicine,” Tata McGraw Hill, NewDelhi-1989.
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