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Department of Public Health & AI (CCP and CAD will be integrated in March 2025)

History

Mar. 2025
Department of Public Health & AI

Overview

Students of the Department of Public Health & AI will develop integrated human resources specialized in cancer prevention and prognosis management. They will utilize the knowledge and skills for public health, epidemiology, public health policy, biostatistics, artificial intelligence, and data science. The program will promote exchanges between industry and academia, while strengthening education and research through the operation of two specific majors: the Major of Public Health and and the Major of AI & Biostatistics.

  • Developing a curriculum that includes Public Health and Artificial Intelligence & Biostatistics
  • Establishment of training infrastructure and systematic training curriculum to enhance practical competency
  • Efficient job connection by activating exchanges with departmental organizations within the National Cancer Center

Methods of education

  • • Mentoring system of full-time and adjunct faculty and industry-academia collaboration
  • • On-the-job training
  • • International research and internship opportunities
Public Health/AI & Biostatistics
Public Health AI & Biostatistics
  • Basic curriculum
    Public Health and Epidemiology
    Biostatistics and Artificial Intelligence
  • In-depth curriculum by major
    Epidemiologic Methodology
    Cancer Epidemiology
    Infectious Disease Epidemiology
    Chronic Disease Epidemiology
    Nutritional Epidemiology
    Omics Epidemiology
    Public Health Economics
    Public Health Policy
  • Applied training course
  • In-depth curriculum by major
    Principles of Biostatistics
    Regression Methods
    Deep Learning and Machine Learning
    Meta-analysis
    Survival Data Analysis
    Spatial Data Analysis
    Data Visualization
    Computer Programming
  • Applied training course
Public Health → fruition AI & Biostatistics → fruition
Combining Public Health and AI-Biostatistics expertise to produce global talent that
can contribute to cancer management and human health promotion

Department of Cancer Control and Population Health (CCP and CAD will be intergrated in March 2025)

History

Mar. 2014
Department of Cancer Control and Policy
Mar. 2017
Department of Cancer Control and Population Health
Mar. 2025
Department of Public Health & AI

Overview

Students in Department of Cancer Control and Population Health will be trained in a relative substantive area and be prepared to perform the national cancer control. The program is an interdisciplinary curriculum covers cancer prevention and control, cancer epidemiology and nutrition, cancer statistics and some other areas.

Graduate Program Credit Requirements (Students admitted in 2019 spring semester ~ 2021 fall semester)

Graduate Program Credit Requirements
Division Core Courses Elective Courses Independent Study(IS) Thesis Research Total
Master’s Program 7 14 6 3 30
Doctoral Program - 18 9 3 30

* Independent Study(IS) can be replaced with elective course

Department of Cancer Biomedical Science

History

Mar. 2014
Department of System Cancer Science
Mar. 2017
Department of Cancer Biomedical Science

Overview

Students in Department of Cancer Biomedical Science will be trained in a relative substantive area and be prepared to study causes of cancer and to establish a plan for cancer therapeutics. The program is an interdisciplinary curriculum covers initiative cancer science, cancer science for system biology and new therapeutics.

Graduate Program Credit Requirements (Students admitted in 2022 spring semester ~ )

Graduate Program Credit Requirements
Division Core Courses Elective Courses Independent Study(IS) Thesis Research Total
Master’s Program 7 14 6 3 30
Doctoral Program - 18 9 3 30

* Independent Study(IS) can be replaced with elective course

Department of Cancer AI & Digital Health (CCP and CAD will be intergrated in March 2025)

History

Mar. 2023
Department of AI & Digital Health
Mar. 2025
Department of Public Health & AI

Overview

Students of the Department of Cancer AI & Digital Health will gain scientific knowledge and technical skills in data science, artificial intelligence, statistics, and informatics. Courses of the program will guide the students to pursue the multidisciplinary application of their knowledge and skills to big data and to perform collaborative research to solve complex questions in epidemiology, health policy and management, and biomedical science related to cancer.

Graduate Program Credit Requirements (Students admitted in 2023 spring semester ~ )

Graduate Program Credit Requirements
Division Core Courses Elective Courses Independent Study(IS) Thesis Research Total
Master’s Program 13 8 6 3 30
Doctoral Program - 18 9 3 30

* Independent Study(IS) can be replaced with elective course Graduate Program Credit Requirements

Track-realted Information

Department of Cancer Control and Population Health
Foundation Core Competencies Specialized Fields of Entry

Master’s degree

  • Learning basic health statistics and analysis methods
  • Grasping computer programming and AI algorithms
  • Understanding structures and processing of various data types (images, signals, EMR, genomics)
Foundation → Core Competencies
  • Practical health data
    management and processing
  • Enhancing statistical analysis skills for
    diverse healthcare data
  • Developing AI capabilities
    for healthcare data types
Core Competencies → Specialized Fields of Entry
  • Clinical trial-related divisions in
    hospitals and pharmaceutics
  • Big data-related departments in
    government agencies
  • Health statistics departments in
    research institutes
  • Medical AI research and solution
    startups and ventures

Doctorate degree

  • Mastering advanced statistical methods for health research
  • Learning advanced programming and AI algorithms
  • Applying sophisticated data processing techniques
Foundation → Core Competencies
  • Cultivating experts in health statistics
    and AI through interdisciplinary research
  • Reinforcing research with advanced AI algorithms tailored to data types
  • Theoretical exploration of new AI
    algorithms and statistical methods for
    advanced cancer research
Core Competencies → Specialized Fields of Entry
  • Clinical trial agencies
    (hospitals and pharma)
  • Health statistics and AI-related
    departments in government
  • Medical AI research and solution
    startups and ventures
  • Experts in health informatics for
    precision medicine in cancer

A Course of Study

암AI디지털헬스학과 석사/박사 과목 안내
  Master’s program   Doctoral program
Core class
  • Deep learning algorithms
  • Principles of biostatistics
  • Regression method in biostatistics
Elective
course
Statistics
  • Introduction to statistical computing
  • Modern health data science
  • Survival data analysis
  • Spatial data analysis
  • Introduction to statistics in genetics
석사 → 박사
  • Health survey design and analysis
  • Advanced statistical methods and modeling
  • Systems epidemiology
Artificial
Intelligence
  • Computer programming language for A.I.
  • Basic mathematics for data science
  • Data processing skills
  • Machine learning algorithms
  • Advanced data science skills
  • Advanced AI algorithms
  • Core or
    Elective (Basic)1st semester

  • Elective (Core)2~3rd semester

  • Field Research4~6th semester

  • Field Research (Core)
    Preparation for thesis7th semester

  • Thesis8th semester