8E500251 Data Literacy in Medicine

Hiroshima University Syllabus

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.

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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