Doctor of Philosophy Program in Data Science for Healthcare and Clinical Informatics
(International Program)

1. Program Title

Doctor of Philosophy Program in Data Science for Healthcare and Clinical Informatics (International Program)

2. Name of Degree

1. Full name: Doctor of Philosophy (Data Science for Healthcare and Clinical Informatics)
2. Abbreviation: Ph.D. (Data Science for Healthcare and Clinical Informatics)

3. Responsible Unit

1. Department of Clinical Epidemiology & Biostatistics, Research Centre, Faculty of Medicine, Ramathibodi Hospital, Mahidol University
2. Faculty of Graduate Studies, Mahidol University

4. The Program’s Philosophy and Objectives

Program Philosophy

The Doctor of Philosophy Program in Data Science for Healthcare and Clinical Informatics (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University aims to build up health professionals (e.g., physicians, pharmacists, dentists, nurses, etc.) and technology professionals (e.g., health informaticians, computer scientists, data scientists, etc.) who are able to process and generate knowledge in related areas including big data, clinical informatics and clinical information systems, data analytics, data visualization, machine Learning, and health research applied to the healthcare system. In addition, graduates should be able to ethically produce good-quality research that can answer health problems of our country and internationally.

Program Objectives

1. Have a good morality and ethics in applying data science and clinical informatics.
2. Integrate knowledge of data science for healthcare and clinical informatics in big data processing and analytics as well as design and management of clinical information systems.
3. Conduct advanced data science and clinical informatics research related to health problems and effectively disseminate research results.
4. Build up capacity to lead a data science and clinical informatics team with a high sense of social responsibility.
5. Integrate mathematical analysis, logical thinking, and information technology and communication skills to management of the healthcare system.

5. Qualifications of Prospective Students

Plan 1 (1.1): Research Only (for Students with a Master’s Degree)

1. Graduated with a Master’s degree in Data Science for Healthcare and Clinical Informatics or a closely-related discipline from an accredited national or international academic institution recognized and attested by the Higher Education Commission
2. Grade point average not less than 3.50
3. Have an English Proficiency Examination score meeting the requirements of the Faculty of Graduate Studies
4. Work or have experience as an instructor or researcher in data sciences or clinical Informatics or closely relevant fields for at least three years
5. Have at least 3 publications in peer-reviewed international journals within the last 5 years, as the first or corresponding author
6. Exemptions from the above conditions may be granted by the Program Committee and the Dean of the Faculty of Graduate Studies under exceptional circumstances.

Plan 2 (2.2): Coursework and Research (for Students with a Bachelor’s Degree)

1. Graduated with a doctor of medicine/dentistry/pharmacy/nursing degree or graduated with a bachelor’s degree in health sciences, information science, mathematics/statistics, engineering, management science, social science, or an IT-related discipline from an accredited national or international academic institution recognized and attested by the Higher Education Commission
2. Grade point average not less than 3.50
3. Have an English Proficiency Examination score meeting the requirements of the Faculty of Graduate Studies
4. Exemptions from the above conditions may be granted by the Program Committee and the Dean of the Faculty of Graduate Studies under exceptional circumstances.

6. Application Procedure:

This is the application procedure:

(1) Please send e-copies of the following:

· Your curriculum vitae,

· Your academic certificates and transcripts,

· Copies of certificates of international examinations in English IELTS Academic 6.0 (writing and speaking no less than 6.0) or TOEFL-IBT 79 (writing no less than 23 and speaking no less than 19) or MU GRAD PLUS 90 (writing and speaking no less than 12) which you have taken,

· Brief outline of your proposed research, it is highly recommended to use our template: 

· At least two reference letters,

· Details of any publications in international journals in English,

· Details of any research experience which you have.

There is no need to submit all prerequisite documents at once. However, should any applicant have alternative documents which are not aligned with the requirements above. Please let us know.

7. Selection Method

This is the process:

1) Selection committee review applicant's information.

2) Selection committee select applicants for interview.

3) Interview in person or by Skype/ZOOM.

4) Notification of result

· Accept / Accept with conditions: Applicant receives a formal acceptance from the Faculty of Graduate Studies which they accept or deny.

· Pending: Applicant is still under consideration and a decision will informed as soon as possible.

· Reject: Applicant is not accepted at this time, but my re-apply in the future.

8. Educational Management System

System: The educational system is of the Semester Credit type. One Academic Year consists of 2 Regular Semesters, each with not less than 15 weeks of study.

Summer Session: There is a 6 week Summer Semester in year 1 or as considered by the Curriculum Administration Committee.

9. Language

English will be used for instruction, written assignments, as well as the writing of dissertation and manuscript.

10. Duration of Study

Plan 1.1: Completion of study must take no more than 5 academic years.
Plan 2.2: Completion of study must take no more than 8 academic years.

11. Evaluation and Graduation Requirements

Evaluation

Student evaluations are in accordance with the rules and regulations of Mahidol University. (See details: www.grad.mahidol.ac.th)

Graduation Requirements (See details: http://www.grad.mahidol.ac.th/en/prospective-students/general-information.php)

Fees: 

Master of Science Program in Data Science for Healthcare and Clinical Informatics
(International Program)

1. Program Title

Master of Science Program in Data Science for Healthcare and Clinical Informatics (International Program)

2. Name of Degree

1. Full name: Master of Science (Data Science for Healthcare and Clinical Informatics)
2. Abbreviation: M.Sc. (Data Science for Healthcare and Clinical Informatics)

3. Responsible Unit

1. Department of Clinical Epidemiology & Biostatistics, Research Centre, Faculty of Medicine, Ramathibodi Hospital, Mahidol University
2. Faculty of Graduate Studies, Mahidol University

4. The Program’s Philosophy and Objectives

Program Philosophy

The Master of Science Program in Data Science for Healthcare and Clinical Informatics (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University aims to build up health professionals (e.g., physicians, pharmacists, dentists, nurses, etc.) and technology professionals (e.g., health informaticians, computer scientists, data scientists etc.) to be able to effectively design, apply, and manage health data and information systems to generate knowledge for the healthcare system. In addition, graduates should be able to ethically produce good-quality research that can answer health problems of our country and internationally.

Program Objectives

1. Have a good morality and ethics in applying data science and clinical informatics.
2. Use knowledge of data science for healthcare and clinical informatics in big data processing and analytics, as well as design and management of clinical information systems.
3. Conduct data science and clinical informatics research related to health problems and effectively disseminate research results.
4. Be a part of a data science and clinical informatics team with a high sense of social responsibility.
5. Apply mathematical analysis, logical thinking, and information technology and communication skills to management of the healthcare system.

5. Qualifications of Prospective Students

1. Graduated with a doctor of medicine/dentistry/pharmacy/nursing degree or graduated with a bachelor’s degree in health sciences, information science, mathematics/statistics, engineering, management science, social science, or an IT-related discipline from an accredited national or international academic institution recognized and attested by the Higher Education Commission
2. Grade point average not less than 2.75
3. Have an English Proficiency Examination score meeting the requirements of the Faculty of Graduate Studies
4. Exemptions from the above conditions may be granted by the Program Committee and the Dean of the Faculty of Graduate Studies under exceptional circumstances.

6. Application Procedure:

This is the application procedure:

1) Please send us e-copies of the following:

· Your curriculum vitae,

· Your academic certificates and transcripts,

· Copies of certificates of international examinations in English IELTS Academic 5.0 (writing and speaking no less than 5.0) or /TOEFL-IBT 64 (writing no less than 17 and speaking no less than 15) or MU GRAD PLUS 70 (writing and speaking no less than 10) which you have taken,

· Brief outline of your proposed research, it is highly recommended to use our template: 

· At least two reference letters

· Details of any publications in international journals in English

· Details of any research experience which you have

You do not need to wait until you have all of these. You can send them as they become available. If any of the above do not apply to you, please inform us.

7. Selection Method

This is the process:

1) Selection committee review applicant's information.

2) Selection committee select applicants for interview.

3) Interview in person or by Skype/ZOOM.

4) Notification of result

· Accept / Accept with conditions: Applicant receives a formal acceptance from the Faculty of Graduate Studies which they accept or deny.

· Pending: Applicant is still under consideration and a decision will informed as soon as possible.

· Reject: Applicant is not accepted at this time, but my re-apply in the future.

8. Educational Management System

System: Two Semester Credit system. 1 Academic Year consists of 2 Regular Semesters, each with not less than 15 weeks of study.

Summer Session: There is a 6 week Summer Semester in year 1 and year 2, or as considered by the Curriculum Administration Committee.

9. Language

English will be used for instruction, written assignments, as well as the writing of dissertation and manuscript.

10. Duration of Study

Completion of study must take no more than 5 academic years.

11. Evaluation and Graduation Requirements

Evaluation

Student evaluations are in accordance with the rules and regulations of Mahidol University. (See details: www.grad.mahidol.ac.th)

Graduation Requirements (See details: http://www.grad.mahidol.ac.th/en/prospective-students/general-information.php)

Fees: 

A. Course Requirements for Ph.D. in Data Science for Healthcare and Clinical Informatics

Required Courses

RADI 607 Theories in Health Informatics and Health Information Technology                                                                            3 (3-0-6)

The health informatics discipline; principles of health information technology application in healthcare; clinical information systems and electronic health records; theories and application of clinical decision support systems; theories on user acceptance of technology and health information technology adoption; theories on change management, project management, unintended consequences of health information technology, and information technology management; information technology infrastructure; software development processes; health information privacy and security; consumer health informatics and mobile health; ethics and law in health informatics; health information exchange; health information standards and interoperability; public policy in health informatics and global health informatics; case study analyses in health informatics and health information technology

RADI 608 Data Mining and Machine Learning                                                                                                                                 3 (2-2-5)

Traditional machine learning techniques applied to healthcare problems; data preprocessing, feature engineering, modeling, evaluation, and deployment; extracting knowledge from various types of data using data mining techniques

RADI 603 Medical Statistics and Programming for Data Science and Clinical Informatics                                                       2 (1-2-3)

Calculus; the probability theory; matrices and vectors; linear algebra; basic python programming; basic R programming; the Structured Query Language

RADI 604 Principles and Concepts of Health Systems                                                                                                                 2 (2-0-4)

Principles and concepts of health policy formulation; advocacy; decision-making; implementation; monitoring and evaluation; systematic assessment of the health policy process; applications of social sciences theories; principles and concepts of health systems; building blocks of health systems; desirable characteristics and goals of health systems; systematic approaches to demand and supply analysis of health services delivery; social determinants of health and health promotion; fundamental concepts of healthcare reforms

RADI 605 Modern Machine Learning                                                                                                                                              2 (1-2-3)

The in-depth coverage of machine learning algorithms; statistical objectives of the prediction; classification and clustering; data validation; cluster analysis; establishing predictive and classification models; using machine learning applications in the health analytics; python programming for modern machine learning

RADI 606 Information Technology Management in Healthcare Organizations                                                                          2 (2-0-4)

Organizational behavior management and the health systems science; strategic management and business-information technology alignment; leadership and teamwork; patient safety and quality improvement; organizational change management; information technology acceptance and adoption; information technology governance; enterprise architecture; information technology project management; information technology risk management; information technology service management; innovation management; case study analyses in information technology management

RADI 609 Research Methods in Data Science and Clinical Informatics                                                                                     2 (2-0-4)

Research proposal writing; literature review; formulating research questions; a selection of data sources; features; measurement; data preprocessing, data analysis planning; research proposal presentations; data visualization; moral and ethics in research

RADI 610 Seminar in Data Science and Clinical Informatics Research                                                                                     2 (2-0-4)

Advances in data science and clinical informatics research; applying knowledge of data science and clinical informatics to real practice; knowledge communication skills in data science and clinical informatics; moral and ethics in data science and clinical informatics; critical appraisals of previous studies and presentations

Elective Courses

RADI 620 Unstructured Data Processing                                                                                                                                      2 (1-2-3)

Essential analytics and programming skills for modern data scientists; applied techniques in real-world setting; understanding various decision-making support techniques

RADI 621 Business Intelligence Systems                                                                                                                                     2 (1-2-3)

Principles of business intelligence systems; data collection and turning data into business values; understanding the data organization; processes and techniques used in extracting, transforming, and loading data; designing the structure of data cubes; building analytics dashboards from business intelligence systems

RADI 622 Medical Image Processing                                                                                                                                             2 (1-2-3)

Knowledge and programming practice of medical imaging modalities; methods of medical image processing; segmentation techniques; volume rendering; 3D object reconstruction; rigid and deformable registration techniques

RADI 623 Natural Language Processing                                                                                                                                       2 (1-2-3)

Programming for natural language processing; language modeling; speech tagging and sequence labeling; syntactic parsing; the semantic analyses; the information extraction; the machine translation

RADI 624 Signal Processing                                                                                                                                                           2 (1-2-3)

Theories and programming practice of representation, transformation, and manipulation of signals in machine readable formats; applying related algorithms to signal processing tasks

RADI 625 Data Modeling and Visualization                                                                                                                                   2 (1-2-3)

Conceptual models of visualization software; principles and value of visualization; quantitative data visualization; qualitative data visualization; the interactive model and animation

RADI 630 Health Information Privacy and Security                                                                                                                      2 (2-0-4)

The information technology infrastructure; principles of information privacy and security; systems security; network security; cryptography; health information privacy and security laws; current situations and trends in information privacy and security; case study analyses in information privacy and security

RADI 631 Operations Management in Healthcare                                                                                                                         2 (2-0-4)

An overview of operations management; the process flow; inventory analysis; managing process variability; application of operations management in healthcare

RADI 632 Information System Development and Management                                                                                                   2 (2-0-4)

An overview of the software life cycle and the software development process; requirements analysis; systems design; software testing; agile development; practice in information system development and management

RADI 633 Public Policy and Laws in Health Informatics                                                                                                              2 (2-0-4)

Public health informatics and public policy; legal systems and basic legal concepts; governance of health information technology in various countries; public policy and laws promoting health information technology governance and adoption; health information privacy and security laws; case study analyses and legal analyses in health informatics

RADI 634 Health Information Standards and Interoperability                                                                                                      2 (2-0-4)

Principles of health information standards and interoperability; the standards development process; terminologies, vocabularies, coding systems, and ontologies; standards in pharmacy; standards for laboratory investigations; standards for medical imaging; standards for diagnoses and clinical documentation; exchange standards; integration of various health information standards

RADI 641 Innovations in Health Information Technology                                                                                                             2 (2-0-4)

Information technology innovations relevant to planning and improvement of the healthcare; clinical decision support systems; advanced tools for patients monitoring and self-care; use of electronic health records (EHRs); e-commerce and the application of current technology in healthcare; factors impacting healthcare innovations

RADI 642 Health Policy Analysis                                                                                                                                                     2 (2-0-4)

A new paradigm of health promotion; the process to change people’s risky behaviors; health promotion for disease control and prevention; policy advocacy for healthy public policy; effectiveness and efficiency of health promotion interventions; concepts of health promotion evaluation

RADI 643 Clinical Decision Support and Artificial Intelligence in Healthcare                                                                             2 (2-0-4)

Clinical decision making, principles of clinical decision support systems; applications of clinical decision support systems and artificial intelligence, design and maintenance of clinical decision support systems; data issues in clinical decision support systems, medical knowledge generation; integration of evidence based medicine, unintended consequences of clinical decision support systems; case study analyses in clinical decision support

B. Course Requirements for M.Sc. in Data Science for Healthcare and Clinical Informatics

Required Courses

RADI 601 Health Informatics and Health Information Technology                                                                                                2 (2-0-4)

The health informatics discipline; principles of health information technology application in healthcare; clinical information systems and electronic health records; information technology management in healthcare organizations; information technology infrastructure; software development processes; health information privacy and security; consumer health informatics and mobile health; health information exchange; health information standards and interoperability; public policy in health informatics; case study analyses in health informatics and health information technology

RADI 602 Data Mining and Knowledge Discovery                                                                                                                           2 (1-2-3)

Concepts and programming practice in knowledge discovery for structured data using data mining methods: classification, clustering, regression, and association analysis; data preprocessing, data transformation, modeling, and evaluation to solve healthcare problems

RADI 603 Medical Statistics and Programming for Data Science and Clinical Informatics                                                         2 (1-2-3)

Calculus; the probability theory; matrices and vectors; linear algebra; basic python programming; basic R programming; the Structured Query Language

RADI 604 Principles and Concepts of Health Systems                                                                                                                    2 (2-0-4)

Principles and concepts of health policy formulation; advocacy; decision-making; implementation; monitoring and evaluation; systematic assessment of the health policy process; applications of social sciences theories; principles and concepts of health systems; building blocks of health systems; desirable characteristics and goals of health systems; systematic approaches to demand and supply analysis of health services delivery; social determinants of health and health promotion; fundamental concepts of healthcare reforms

RADI 605 Modern Machine Learning                                                                                                                                                  2 (1-2-3)

The in-depth coverage of machine learning algorithms; statistical objectives of the prediction; classification and clustering; data validation; cluster analysis; establishing predictive and classification models; using machine learning applications in the health analytics; python programming for modern machine learning

RADI 606 Information Technology Management in Healthcare Organizations                                                                               2 (2-0-4)

Organizational behavior management and the health systems science; strategic management and business-information technology alignment; leadership and teamwork; patient safety and quality improvement; organizational change management; information technology acceptance and adoption; information technology governance; enterprise architecture; information technology project management; information technology risk management; information technology service management; innovation management; case study analyses in information technology management

RADI 609 Research Methods in Data Science and Clinical Informatics                                                                                          2 (2-0-4)

Research proposal writing; literature review; formulating research questions; a selection of data sources; features; measurement; data preprocessing, data analysis planning; research proposal presentations; data visualization; moral and ethics in research

RADI 610 Seminar in Data Science and Clinical Informatics Research                                                                                          2 (2-0-4)

Advances in data science and clinical informatics research; applying knowledge of data science and clinical informatics to real practice; knowledge communication skills in data science and clinical informatics; moral and ethics in data science and clinical informatics; critical appraisals of previous studies and presentations

Elective Courses

RADI 620 Unstructured Data Processing                                                                                                                                           2 (1-2-3)

Essential analytics and programming skills for modern data scientists; applied techniques in real-world setting; understanding various decision-making support techniques

RADI 621 Business Intelligence Systems                                                                                                                                          2 (1-2-3)

Principles of business intelligence systems; data collection and turning data into business values; understanding the data organization; processes and techniques used in extracting, transforming, and loading data; designing the structure of data cubes; building analytics dashboards from business intelligence systems

RADI 622 Medical Image Processing                                                                                                                                                  2 (1-2-3)

Knowledge and programming practice of medical imaging modalities; methods of medical image processing; segmentation techniques; volume rendering; 3D object reconstruction; rigid and deformable registration techniques

RADI 623 Natural Language Processing                                                                                                                                            2 (1-2-3)

Programming for natural language processing; language modeling; speech tagging and sequence labeling; syntactic parsing; the semantic analyses; the information extraction; the machine translation

RADI 624 Signal Processing                                                                                                                                                                2 (1-2-3)

Theories and programming practice of representation, transformation, and manipulation of signals in machine readable formats; applying related algorithms to signal processing tasks

RADI 630 Health Information Privacy and Security                                                                                                                           2 (2-0-4)

The information technology infrastructure; principles of information privacy and security; systems security; network security; cryptography; health information privacy and security laws; current situations and trends in information privacy and security; case study analyses in information privacy and security

RADI 631 Operations Management in Healthcare                                                                                                                              2 (2-0-4)

An overview of operations management; the process flow; inventory analysis; managing process variability; application of operations management in healthcare

RADI 632 Information System Development and Management                                                                                                        2 (2-0-4)

An overview of the software life cycle and the software development process; requirements analysis; systems design; software testing; agile development; practice in information system development and management

RADI 633 Public Policy and Laws in Health Informatics                                                                                                                   2 (2-0-4)

Public health informatics and public policy; legal systems and basic legal concepts; governance of health information technology in various countries; public policy and laws promoting health information technology governance and adoption; health information privacy and security laws; case study analyses and legal analyses in health informatics

RADI 634 Health Information Standards and Interoperability                                                                                                           2 (2-0-4)

Principles of health information standards and interoperability; the standards development process; terminologies, vocabularies, coding systems, and ontologies; standards in pharmacy; standards for laboratory investigations; standards for medical imaging; standards for diagnoses and clinical documentation; exchange standards; integration of various health information standards

RADI 641 Innovations in Health Information Technology                                                                                                                  2 (2-0-4)

Information technology innovations relevant to planning and improvement of the healthcare; clinical decision support systems; advanced tools for patients monitoring and self-care; use of electronic health records (EHRs); e-commerce and the application of current technology in healthcare; factors impacting healthcare innovations

RADI 642 Health Policy Analysis                                                                                                                                                          2 (2-0-4)

A new paradigm of health promotion; the process to change people’s risky behaviors; health promotion for disease control and prevention; policy advocacy for healthy public policy; effectiveness and efficiency of health promotion interventions; concepts of health promotion evaluation

RADI 643 Clinical Decision Support and Artificial Intelligence in Healthcare                                                                                  2 (2-0-4)

Clinical decision making, principles of clinical decision support systems; applications of clinical decision support systems and artificial intelligence, design and maintenance of clinical decision support systems; data issues in clinical decision support systems, medical knowledge generation; integration of evidence based medicine, unintended consequences of clinical decision support systems; case study analyses in clinical decision support