Hiroshima University Syllabus

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Japanese
Academic Year 2024Year School/Graduate School Common Graduate Courses (Doctoral Course)
Lecture Code 8E550451 Subject Classification Common Graduate Courses
Subject Name 医療情報リテラシー活用[オンデマンド]
Subject Name
(Katakana)
イリョウジョウホウリテラシーカツヨウ[オンデマンド]
Subject Name in
English
Utilization of data Literacy in Medicine[On-Demand]
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) Thur11-12:Online
Lesson Style Lecture Lesson Style
(More Details)
 
Utilization of 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 博士課程後期
Keywords Big data, Genome information, Medical research, Clinical research, Information security, Ethics 
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.
※This is an on-demand class offered to students with difficulty attending school during regular hours. 
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, etc. 
Class Schedule lesson1 (October 3)Classifications and outlines of large medical databases such as National Data Base (NDB)<on-demand>
lesson2 (October 10)Use and issues of data from vital statistics and National Cancer Registry and their use in epidemiological studies <on-demand>
lesson3 (October 17)Classifications of genomic information, merits, demerits and usefulness for research using genomic information <on-demand>
lesson4 (October 24)Issues in utilization of Real World Data in the Medical Field: In the viewpoint of “Hospital Information Systems" <on-demand>
lesson5 (October 31)Overview of cancer genome information, challenges, and its application and utilization <live stream>
lesson6 (Nobember 14)How to establish standard clinical data set during emergencies, and application and utilization of it <on-demand>
lesson7 (Nobember 21)Data science in medical study <on-demand>
lesson8 (Nobember 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)  
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
Review handout 
Requirements This course is one of the on-demand courses offered for those who have difficulty attending school during regular hours (doctoral course). All students are eligible to take these on-demand classes, but there are a limited number of places. Priority will be given to those who have filled out the priority registration request form and stated that they are unable to take the course during regular hours. Remaining places will be allocated to other students by computerized random selection. Please check the following URL for further details.
https://momiji.hiroshima-u.ac.jp/momiji-top/en/learning/cgcinfo-d-1.html 
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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