8E550451 Utilization of data Literacy in Medicine

Hiroshima University Syllabus

Japanese

Academic Year 2025Year 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

Subject Name
（Katakana）イリョウジョウホウリテラシーカツヨウ

Subject Name in
English Utilization of data Literacy in Medicine

Instructor AKITA TOMOYUKI,YOSHINAGA SHINJI,TAKASAKI YOSUKE,ABE SHINICHI,MIKI DAIKI,KUBO TATSUHIKO,HINOI TAKAO,TANAKA TAKESHI,SUGIYAMA AYA

Instructor
(Katakana) アキタ　トモユキ,ヨシナガ　シンジ,タカサキ　ヨウスケ,アベ　シンイチ,ミキ　ダイキ,クボ　タツヒコ,ヒノイ　タカオ,タナカ　タケシ,スギヤマ　アヤ

Campus Kasumi Semester/Term 1st-Year, Second Semester, 3Term

Days, Periods, and Classrooms (3T) Thur11-12：Online

Lesson Style Lecture Lesson Style
(More Details) Online (simultaneous interactive), Online (on-demand)

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 2 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 Epidemiology, Big data, Genome information, Medical research, Clinical research, Medical Information

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 In medical research, the importance of fields dealing with medical information is increasing. This includes the development of new cancer treatments using cancer genome information, clinical research aimed at establishing effective therapies, and epidemiological studies utilizing medical records, which have become accessible as big data due to the widespread use of electronic health records.
Therefore, to excel in future healthcare-related fields, it is essential to learn how to handle various types of medical information, including ethical considerations such as personal data protection.
This course, based on the participants' fundamental knowledge of medicine and healthcare, provides basic explanations and practical exercises on the knowledge and techniques necessary for the appropriate handling, processing, and analysis of medical information.

Class Schedule lesson1　（October 2）Guidance, Acquisition and Utilization of Medical Information in Epidemiological Research<on-demand>
lesson2　（October 9）Use and issues of data from vital statistics and National Cancer Registry and their use in epidemiological studies <on-demand>
lesson3　（October 23）Classifications of genomic information, merits, demerits and usefulness for research using genomic information <on-demand>
lesson4　（October 30）Issues in utilization of Real World Data in the Medical Field: In the viewpoint of “Hospital Information Systems" <live stream>
lesson5　（November 6）Overview of cancer genome information, challenges, and its application and utilization <on-demand>
lesson6　（November 13）How to establish standard clinical data set during emergencies, and application and utilization of it <on-demand>
lesson7 （November 20）Digital technology in Healthcare Field: Application, future prospect and challenges　<live stream>
lesson8 （November 27）Latest Trends in Data Science for Medical Research: From Handling Medical Big Data to Utilizing DX and AI <on-demand>

After each lecture, students are required to submit a report and practical work results. Reports should be submitted using Microsoft Forms (or the Dropbox file upload system if necessary). The URLs for Microsoft Forms and other submission platforms will be posted on Momiji and Moodle.

A final report will be assigned.

Text/Reference
Books,etc. Due to the broad scope of the lecture content, no specific textbook will be designated. There are numerous books available on topics covered in the lectures, such as epidemiology, medical informatics, and genomic medicine. Students are encouraged to refer to those that best suit their needs.

PC or AV used in
Class,etc. Handouts, Microsoft Teams, Microsoft Stream, Microsoft Forms, moodle

(More Details)

Learning techniques to be incorporated Discussions, Quizzes/ Quiz format, PBL (Problem-based Learning)/ TBL (Team-based Learning), Post-class Report

Suggestions on
Preparation and
Review With the advancement of information technology and data analysis techniques, as well as revisions to ethical guidelines and personal information protection laws, the concept of appropriate handling of medical information is evolving each year. This course presents several case studies in the medical field and encourages students to consider the appropriate utilization of medical information in their respective areas based on the lecture content.

Requirements ・Basic medical knowledge is assumed. (Although non-medical graduate students may take this course, no special consideration will be given. If you feel that your knowledge is insufficient, you are expected to take an active learning approach by asking questions or conducting independent research.)
・This course includes exercises and practical sessions, which may require additional time beyond video lectures.
・This course is designed to accommodate international students, and each instructor provides English support to meet the required standards.
・The course includes both on-demand and live lectures, each with designated viewing periods and assignment submission deadlines. Be sure to check and adhere to these deadlines.
・Any academic misconduct, such as plagiarism in assignments or disruptive behavior, will result in the immediate denial of course credit.
・Unless otherwise specified, do not use generative AI for report writing. If more than 70% of the content is suspected to be copied or generated by AI, as determined by a detection tool, the report may not be accepted after careful review.
By enrolling in this course, you acknowledge and agree to these conditions.

Grading Method Report submission after each lecture (submitted via Microsoft Forms) (60%)/Final report (40%)
＊This serves as an evaluation of lecture attendance and engagement. Significant point deductions will be applied if the report contains extremely little content or if it is unclear from the content whether the lecture video was actually attended.
Each report will be graded on a 10-point scale, and the six highest scores will be used for evaluation.
The final report will consist of written-response questions. Students will have the option to either submit a summary of all eight lectures in the form of handwritten or typed notes (e.g., Word document) or select and answer questions from multiple question sets related to the lecture content of each session.

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 This course is designed for international students, and the language of instruction is set to "English-supported." Depending on the instructor, different approaches may be used, such as alternating explanations in Japanese and English, conducting the lecture entirely in English, or providing slides with both Japanese and English text. Please take this into consideration before enrolling.

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	2025Year	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
Subject Name （Katakana）	イリョウジョウホウリテラシーカツヨウ
Subject Name in English	Utilization of data Literacy in Medicine
Instructor	AKITA TOMOYUKI,YOSHINAGA SHINJI,TAKASAKI YOSUKE,ABE SHINICHI,MIKI DAIKI,KUBO TATSUHIKO,HINOI TAKAO,TANAKA TAKESHI,SUGIYAMA AYA
Instructor (Katakana)	アキタ　トモユキ,ヨシナガ　シンジ,タカサキ　ヨウスケ,アベ　シンイチ,ミキ　ダイキ,クボ　タツヒコ,ヒノイ　タカオ,タナカ　タケシ,スギヤマ　アヤ
Campus	Kasumi	Semester/Term	1st-Year, Second Semester, 3Term
Days, Periods, and Classrooms	(3T) Thur11-12：Online
Lesson Style	Lecture	Lesson Style (More Details)	Online (simultaneous interactive), Online (on-demand)
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	2	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	Epidemiology, Big data, Genome information, Medical research, Clinical research, Medical Information
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	In medical research, the importance of fields dealing with medical information is increasing. This includes the development of new cancer treatments using cancer genome information, clinical research aimed at establishing effective therapies, and epidemiological studies utilizing medical records, which have become accessible as big data due to the widespread use of electronic health records. Therefore, to excel in future healthcare-related fields, it is essential to learn how to handle various types of medical information, including ethical considerations such as personal data protection. This course, based on the participants' fundamental knowledge of medicine and healthcare, provides basic explanations and practical exercises on the knowledge and techniques necessary for the appropriate handling, processing, and analysis of medical information.
Class Schedule	lesson1　（October 2）Guidance, Acquisition and Utilization of Medical Information in Epidemiological Research<on-demand> lesson2　（October 9）Use and issues of data from vital statistics and National Cancer Registry and their use in epidemiological studies <on-demand> lesson3　（October 23）Classifications of genomic information, merits, demerits and usefulness for research using genomic information <on-demand> lesson4　（October 30）Issues in utilization of Real World Data in the Medical Field: In the viewpoint of “Hospital Information Systems" <live stream> lesson5　（November 6）Overview of cancer genome information, challenges, and its application and utilization <on-demand> lesson6　（November 13）How to establish standard clinical data set during emergencies, and application and utilization of it <on-demand> lesson7 （November 20）Digital technology in Healthcare Field: Application, future prospect and challenges　<live stream> lesson8 （November 27）Latest Trends in Data Science for Medical Research: From Handling Medical Big Data to Utilizing DX and AI <on-demand> After each lecture, students are required to submit a report and practical work results. Reports should be submitted using Microsoft Forms (or the Dropbox file upload system if necessary). The URLs for Microsoft Forms and other submission platforms will be posted on Momiji and Moodle. A final report will be assigned.
Text/Reference Books,etc.	Due to the broad scope of the lecture content, no specific textbook will be designated. There are numerous books available on topics covered in the lectures, such as epidemiology, medical informatics, and genomic medicine. Students are encouraged to refer to those that best suit their needs.
PC or AV used in Class,etc.	Handouts, Microsoft Teams, Microsoft Stream, Microsoft Forms, moodle
(More Details)
Learning techniques to be incorporated	Discussions, Quizzes/ Quiz format, PBL (Problem-based Learning)/ TBL (Team-based Learning), Post-class Report
Suggestions on Preparation and Review	With the advancement of information technology and data analysis techniques, as well as revisions to ethical guidelines and personal information protection laws, the concept of appropriate handling of medical information is evolving each year. This course presents several case studies in the medical field and encourages students to consider the appropriate utilization of medical information in their respective areas based on the lecture content.
Requirements	・Basic medical knowledge is assumed. (Although non-medical graduate students may take this course, no special consideration will be given. If you feel that your knowledge is insufficient, you are expected to take an active learning approach by asking questions or conducting independent research.) ・This course includes exercises and practical sessions, which may require additional time beyond video lectures. ・This course is designed to accommodate international students, and each instructor provides English support to meet the required standards. ・The course includes both on-demand and live lectures, each with designated viewing periods and assignment submission deadlines. Be sure to check and adhere to these deadlines. ・Any academic misconduct, such as plagiarism in assignments or disruptive behavior, will result in the immediate denial of course credit. ・Unless otherwise specified, do not use generative AI for report writing. If more than 70% of the content is suspected to be copied or generated by AI, as determined by a detection tool, the report may not be accepted after careful review. By enrolling in this course, you acknowledge and agree to these conditions.
Grading Method	Report submission after each lecture (submitted via Microsoft Forms) (60%)/Final report (40%) ＊This serves as an evaluation of lecture attendance and engagement. Significant point deductions will be applied if the report contains extremely little content or if it is unclear from the content whether the lecture video was actually attended. Each report will be graded on a 10-point scale, and the six highest scores will be used for evaluation. The final report will consist of written-response questions. Students will have the option to either submit a summary of all eight lectures in the form of handwritten or typed notes (e.g., Word document) or select and answer questions from multiple question sets related to the lecture content of each session.
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	This course is designed for international students, and the language of instruction is set to "English-supported." Depending on the instructor, different approaches may be used, such as alternating explanations in Japanese and English, conducting the lecture entirely in English, or providing slides with both Japanese and English text. Please take this into consideration before enrolling.
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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