Hiroshima University Syllabus

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Japanese
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. 
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   
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. 
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