Academic Year |
2025Year |
School/Graduate School |
Graduate School of Biomedical and Health Sciences (Master’s Course) |
Lecture Code |
TB000261 |
Subject Classification |
Specialized Education |
Subject Name |
特別研究 |
Subject Name (Katakana) |
トクベツケンキュウ |
Subject Name in English |
Research |
Instructor |
FUKUMA SHINGO,KO KO,AKITA TOMOYUKI,SUGIYAMA AYA |
Instructor (Katakana) |
フクマ シンゴ,コ コ,アキタ トモユキ,スギヤマ アヤ |
Campus |
Kasumi |
Semester/Term |
1st-Year, Second Semester, Second Semester |
Days, Periods, and Classrooms |
(2nd) Inte:Clinical Departments |
Lesson Style |
Experiment |
Lesson Style (More Details) |
Face-to-face |
Lecture and Experiment |
Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
J
:
Japanese |
Course Level |
7
:
Graduate Special Studies
|
Course Area(Area) |
27
:
Health Sciences |
Course Area(Discipline) |
01
:
Medical Sciences |
Eligible Students |
Doctor's course students |
Keywords |
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Special Subject for Teacher Education |
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Special Subject |
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Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students) | |
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Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students) | |
Class Objectives /Class Outline |
Students will learn about the epidemiological methodology to analyze large and diverse health and medical data and solve society's health problems. Students will also learn about statistics, data science, clinical medicine, behavioral science, health policy, and health economics. In practicing epidemiological research, students will acquire the logic and skills to set their own research questions, organize research design, create a research plan, analyze data, and write a paper.
This class contains Review of text or paper, seminar, laboratory experiment, field research, data analysis, seminar etc. under the guidance of supervisor.
The following lecture plan will be modified flexibly according to the students' research topics. This class contains Review of text or paper, seminar, laboratory experiment, field research, data analysis, seminar etc. under the guidance of supervisor.
The following lecture plan will be modified flexibly according to the students' research topics. |
Class Schedule |
1. survey of previous studies - 1 2. survey of previous studies - 2 3. structure of large-scale health data-1 4. Structure of Large-Scale Health Data - 2 5. Research Hypothesis - 1 6. Research Hypothesis - 2 7. Causal inference using statistical and mathematical models, and classification and prediction using machine learning models-1 8. causal inference using statistical and mathematical models, and classification and prediction using machine learning models - 2 9. design of analysis-1 10. design of analysis-2 11. implementation of data analysis-1 12. implementation of data analysis-2 13. review and interpretation of analysis results -1 14. review and interpretation of analysis results - 2 15. presentation |
Text/Reference Books,etc. |
Handouts |
PC or AV used in Class,etc. |
Text, Handouts, Microsoft Teams |
(More Details) |
Slide |
Learning techniques to be incorporated |
Discussions, PBL (Problem-based Learning)/ TBL (Team-based Learning), Project Learning, Flip Teaching, Post-class Report |
Suggestions on Preparation and Review |
As for seminar presentation, please prepare thoroughly and review the points you received during the seminar. Also, pay attention to other students' presentations and comments on them. The slides used in the presentation will be evaluated, so please make any revisions after the presentation before submitting. |
Requirements |
Graduate students who belong to laboratories other than Epidemiology, Disease Control and Prevention and who wish to take this course should contact Tomoyuki Akita, Lecturer, during April (October) regarding the content of the exercises. |
Grading Method |
Report |
Practical Experience |
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Summary of Practical Experience and Class Contents based on it |
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Message |
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Other |
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Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching. |