Molecular Oncology (DR) Preview
PhD	TR-NQF-HE: Level 8	QF-EHEA: Third Cycle	EQF-LLL: Level 8

Course Introduction and Application Information

Course Code:

MONK6014

Course Name:

Bioinformatics and Artificial Intelligence in Cancer 2

Semester:

Fall

Course Credits:

ECTS

Language of instruction:

Turkish

Course Condition:

Does the Course Require Work Experience?:

Yes

Type of course:

Departmental Elective

Course Level:

PhD

TR-NQF-HE:8. Master`s Degree

QF-EHEA:Third Cycle

EQF-LLL:8. Master`s Degree

Mode of Delivery:

E-Learning

Course Coordinator:

Dr. Öğr. Üy. LEVENT KORKMAZ

Course Lecturer(s):

Levent Korkmaz

Course Assistants:

Course Objective and Content

Course Objectives:	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
Course Content:	Oncological data and artificial intelligence modeling constructs will be explained.

Learning Outcomes

The students who have succeeded in this course;

Course Flow Plan

Week	Subject	Related Preparation
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes
1)	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes	Data mining and decision support systems - Clinical data profiling in cancer Designing statistical and machine learning models in oncology clinical practice, constructing cancer artificial intelligence nodes

Sources

Course Notes / Textbooks:	-
References:	-

Course - Program Learning Outcome Relationship

Course Learning Outcomes
Program Outcomes
1) To be able to define, evaluate and use current and advanced knowledge of cancer and molecular cancer
2) To be able to research, comprehend and analyze a scientific and technological issue in the field of molecular cancer with a systematic approach.
3) Ability to develop, design, adapt and implement new and complex ideas about the molecular mechanisms of cancer at an expert level with original thinking and/or research
4) To be able to comprehend the interdisciplinary interaction with which the molecular cancer field is related, to develop a new method, design and/or application with a new idea or a known idea.
5) To gain the ability to synthesize, analyze, interpret, question and criticize information about treatment approaches developed against cancer
6) Tp develop new ideas and methods in the field by using high-level skills such as problem solving and decision making in their studies.
7) To have good communication skills in their work and being able to critically examine and develop the norms that guide these relationships, and to manage actions to change them when necessary
8) To have an awareness of ethical responsibility in their research and to be able to defend their findings by using advanced written, verbal and visual communication.
9) To contribute to the solution of social, scientific, computational and ethical problems encountered in the field of molecular cancer and to support the development of these values.
10) To be able to interpret research and study results and expand the limits of knowledge in the field by producing an original work.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Average	3 Highest

	Program Outcomes	Level of Contribution
1)	To be able to define, evaluate and use current and advanced knowledge of cancer and molecular cancer
2)	To be able to research, comprehend and analyze a scientific and technological issue in the field of molecular cancer with a systematic approach.
3)	Ability to develop, design, adapt and implement new and complex ideas about the molecular mechanisms of cancer at an expert level with original thinking and/or research
4)	To be able to comprehend the interdisciplinary interaction with which the molecular cancer field is related, to develop a new method, design and/or application with a new idea or a known idea.
5)	To gain the ability to synthesize, analyze, interpret, question and criticize information about treatment approaches developed against cancer
6)	Tp develop new ideas and methods in the field by using high-level skills such as problem solving and decision making in their studies.
7)	To have good communication skills in their work and being able to critically examine and develop the norms that guide these relationships, and to manage actions to change them when necessary
8)	To have an awareness of ethical responsibility in their research and to be able to defend their findings by using advanced written, verbal and visual communication.
9)	To contribute to the solution of social, scientific, computational and ethical problems encountered in the field of molecular cancer and to support the development of these values.
10)	To be able to interpret research and study results and expand the limits of knowledge in the field by producing an original work.

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
total		%

Workload and ECTS Credit Calculation

Activities	Number of Activities	Preparation for the Activity	Spent for the Activity Itself	Completing the Activity Requirements	Workload
Course Hours	3	0			0
Homework Assignments	1	1			1
Final	1	0			0
Total Workload					1