8E550451 Utilization of data Literacy in Medicine[On-Demand]

Hiroshima University Syllabus

Japanese

Academic Year 2022Year 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 TANAKA JUNKO,ABE SHINICHI,YOSHIMURA KENICHI,MIHARA NAOKI,MIKI DAIKI,KUBO TATSUHIKO,OUE NAOHIDE

Instructor
(Katakana) タナカ　ジュンコ,アベ　シンイチ,ヨシムラ　ケンイチ,ミハラ　ナオキ,ミキ　ダイキ,クボ　タツヒコ,オオウエ　ナオヒデ

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 This course is one of the elective subjects, in "Career Development and Data Literacy Courses", Common Graduate Courses that aims to learn about the development of the current social systems, to gain knowledge needed for the future, to specifically tackle the challenges facing modern society and to acquire the ability to use knowledge and skills.
Criterion referenced
Evaluation

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　Classifications and outlines of large medical databases such as National Data Base (NDB)
lesson2　Literacy in the clinical research data interpretation
lesson3　Classifications of genomic information, merits, demerits and usefulness for research using genomic information
lesson4　Issues in utilization of Real World Data in the Medical Field: In the viewpoint of “Hospital Information Systems"
lesson5　Overview of cancer genome information and challenges
lesson6　How to establish standard clinical data set during emergencies
lesson7　TBD
lesson8　Data / AI in Healthcare Field: Application, Future prospect and challenging points (Lecturer: A head of Google
Cloud Japan, Mr.Abe)

Only report

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 subject to the priority adoption request form for course registration of Common Graduate Courses (Doctoral Course).All students are eligible to take these classes, but there are a limited number of places. Priority will be given to those who have filled out a request form because they are unable to take the course during the regular hours. Remaining places will be allocated on the basis of a random computerized draw. Please check the following URL for details.
https://momiji.hiroshima-u.ac.jp/momiji-top/en/learning/cgcinfo-d-1.html

Grading Method Attendance, Report
Submit report every time by using Microsoft FORMS.
The URL for Microsoft FORMS will be posted on Bb9.

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.

Academic Year	2022Year	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	TANAKA JUNKO,ABE SHINICHI,YOSHIMURA KENICHI,MIHARA NAOKI,MIKI DAIKI,KUBO TATSUHIKO,OUE NAOHIDE
Instructor (Katakana)	タナカ　ジュンコ,アベ　シンイチ,ヨシムラ　ケンイチ,ミハラ　ナオキ,ミキ　ダイキ,クボ　タツヒコ,オオウエ　ナオヒデ
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	This course is one of the elective subjects, in "Career Development and Data Literacy Courses", Common Graduate Courses that aims to learn about the development of the current social systems, to gain knowledge needed for the future, to specifically tackle the challenges facing modern society and to acquire the ability to use knowledge and skills.
Criterion referenced Evaluation
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　Classifications and outlines of large medical databases such as National Data Base (NDB) lesson2　Literacy in the clinical research data interpretation lesson3　Classifications of genomic information, merits, demerits and usefulness for research using genomic information lesson4　Issues in utilization of Real World Data in the Medical Field: In the viewpoint of “Hospital Information Systems" lesson5　Overview of cancer genome information and challenges lesson6　How to establish standard clinical data set during emergencies lesson7　TBD lesson8　Data / AI in Healthcare Field: Application, Future prospect and challenging points (Lecturer: A head of Google Cloud Japan, Mr.Abe) Only report
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 subject to the priority adoption request form for course registration of Common Graduate Courses (Doctoral Course).All students are eligible to take these classes, but there are a limited number of places. Priority will be given to those who have filled out a request form because they are unable to take the course during the regular hours. Remaining places will be allocated on the basis of a random computerized draw. Please check the following URL for details. https://momiji.hiroshima-u.ac.jp/momiji-top/en/learning/cgcinfo-d-1.html
Grading Method	Attendance, Report Submit report every time by using Microsoft FORMS. The URL for Microsoft FORMS will be posted on Bb9.
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.

Back to syllabus main page