Academic Year |
2024Year |
School/Graduate School |
Common Graduate Courses (Master’s Course) |
Lecture Code |
8E500251 |
Subject Classification |
Common Graduate Courses |
Subject Name |
医療情報リテラシー |
Subject Name (Katakana) |
イリョウジョウホウリテラシー |
Subject Name in English |
Data Literacy in Medicine |
Instructor |
AKITA TOMOYUKI,YOSHINAGA SHINJI,ABE SHINICHI,MIHARA NAOKI,MIKI DAIKI,KUBO TATSUHIKO,TANAKA JUNKO,HINOI TAKAO |
Instructor (Katakana) |
アキタ トモユキ,ヨシナガ シンジ,アベ シンイチ,ミハラ ナオキ,ミキ ダイキ,クボ タツヒコ,タナカ ジュンコ,ヒノイ タカオ |
Campus |
Kasumi |
Semester/Term |
1st-Year, Second Semester, 3Term |
Days, Periods, and Classrooms |
(3T) Thur13-14:Online |
Lesson Style |
Lecture |
Lesson Style (More Details) |
|
Data Literacy in Medicine will be held as an Online lecture. There are lectures delivered on-demand and live stream. For on-demand lectures, please take the lecture within one week from the scheduled lecture date. In the case of live stream lecture, please be sure to attend during the scheduled lecture time. Only if you cannot take the live lecture on time, you can receive the recorded lecture. |
Credits |
1.0 |
Class Hours/Week |
|
Language of Instruction |
B
:
Japanese/English |
Course Level |
7
:
Graduate Special Studies
|
Course Area(Area) |
27
:
Health Sciences |
Course Area(Discipline) |
01
:
Medical Sciences |
Eligible Students |
Master's course |
Keywords |
Big data, Genome information, Medical research, Clinical research, Information security, Ethics,Law |
Special Subject for Teacher Education |
|
Special Subject |
|
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students) | This course is one of the elective subjects in the category of "Career Development and Data Literacy Courses" for Common Graduate Courses. This category of courses aims to provide opportunities for students to learn about the development of the current social systems, to gain knowledge needed for the future, to concretely tackle the challenges facing modern society, and to acquire the ability to utilize knowledge and skills. |
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Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students) | |
Class Objectives /Class Outline |
To learn basic explanations about the knowledge required to process medical information, as well as information security,ethics, laws,etc. |
Class Schedule |
lesson1 (10/3)Classifications and outlines of large medical databases such as National Data Base (NDB) <on-demand> lesson2 (10/10)Use of data from vital statistics and National Cancer Registry and their use in epidemiological studies <on-demand> lesson3 (10/17)Classifications of genomic information, merits, demerits and usefulness for research using genomic information <on-demand> lesson4 (10/24)Types of medical data, system issues, and usefulness of information in the medical field <on-demand> lesson5 (10/31)Overview of cancer genome information and challenges <live stream> lesson6 (11/14)How to establish standard clinical data set during emergencies <on-demand> lesson7 (11/21)Data science in medical study <on-demand> lesson8 (11/28)Digital technology in Healthcare Field: Application, future prospect and challenges <live stream>
Submitting a report every time is mandatory by using Microsoft Forms. The submission URL will be posted on moodle. |
Text/Reference Books,etc. |
Handout |
PC or AV used in Class,etc. |
|
(More Details) |
Handout・Picture(Video/PC/Other) |
Learning techniques to be incorporated |
|
Suggestions on Preparation and Review |
Review handout |
Requirements |
|
Grading Method |
Evaluate the content of the reports, and the attitude of participating in the class (100%) |
Practical Experience |
Experienced
|
Summary of Practical Experience and Class Contents based on it |
A head of EMNES will give a lecture of big data and AI technology in health care field. |
Message |
|
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. |