Master of Science in Health Analytics (Mixed-mode) | PolyU SPEED

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Master of Science in Health Analytics (Mixed-mode)

Master of Science in Health Analytics (Mixed-mode)

Programme Code

84613-HAF / 84613-HAP (Full-time / Part-time)

Medium of Instruction

English

Programme Leader

Dr Simon CHEUNG

BSc (Br.Col.), MSc (C.U.H.K.), EdD (Brist.); FACHSM, FHKCHSE

Assistant Programme Leader

Dr Hon-sun CHIU

BEng, MEd, MPhil, PhD (H.K.); Council Member (Hong Kong Survey and Policy Research Association); Life Full Member (iProA)

Tuition Fee

Tuition Fee

Normal Duration

1 year (Full-time) / 2 years (Part-time)

Academic Division

Division of Science, Engineering and Health Studies

Intake

The programme offers two intakes per academic year, i.e. September and January.

Programme Features

  • The programme will empower students with the expertise needed to harness the power of health analytics and AI to transform healthcare delivery. By focusing on the convergence of AI, data analysis, and healthcare management, the programme equips graduates with the skills to leverage AI-driven insights to streamline healthcare operations and foster innovation. Through equipping students with theoretical knowledge and practical skills, they will learn to apply AI techniques across a wide range of healthcare applications, including diagnostics, treatment planning, predictive modelling, medical research, and health informatics, for improved healthcare outcomes. 

 

In summary, the MSc in Health Analytics features:

  • Cutting-Edge Curriculum: The program offers a comprehensive curriculum that combines health analytics with artificial intelligence, preparing students to leverage data for improved healthcare outcomes.
  • Focus on Emerging Technologies: Students will learn to apply advanced techniques in AI and data analytics specifically within healthcare settings, addressing current industry challenges and trends.
  • Real-World Applications: The program emphasizes practical experience, including opportunities for students to engage with healthcare professionals.

Future Prospects

    Career Prospects

    • Graduates of this proposed programme will be well-positioned to meet the growing demand for health analytics and AI expertise in Hong Kong. Key areas of employment span across public and private healthcare sectors, primary healthcare services, technology and innovation, as well as research and academia. 

     

    Further Study Opportunities

    • Upon completion of this programme, graduates may: 
      ⮚ pursue doctoral degree programmes in both local and international universities. 

    Professional Recognition

    The programme will seek accreditation from the following professional bodies:

    • Hong Kong Society of Medical Informatics (HKSMI)
    • Hong Kong College of Community Health Practitioners (HKCCHP)
    • International Medical Informatics Association (IMIA)
    • American Medical Informatics Association (AMIA)
    • European Federation for Medical Informatics (EFMI)

    Programme Structure

    Students are required to complete 11 subjects for a total of 31 credits** with satisfactory results as well as passing an e-learning course (non-credit bearing), namely “Understanding China and the Hong Kong Special Administrative Region, P.R.C.”, to fulfil the National Education Requirement in order to obtain a master’s degree.
     
    Classes will be scheduled on weekdays and / or weekends, both during the day and / or evening, to provide flexibility. They may also be arranged in block teaching format. Please plan accordingly to ensure your availability.

     

    The subject list below will be reviewed from time to time and will be updated without prior notice. 

     

    Compulsory Subjects (9-11 subjects, 3 credits each unless otherwise specified) 

    • Academic Integrity and Healthcare Ethics (1 credit)
    • AI-driven Cybersecurity Management
    • AI Governance, Ethics, and Sustainability in Health Analytics
    • Artificial Intelligence and Digital Health
    • Health Data Management and Analytic Systems
    • Integrated Project
    • IoT and Wearables for AI-Driven Healthcare@
    • Laws and Ethics in Healthcare
    • Low-code to No-code AI Solutions^
    • Quality Assurance and Safety in Healthcare Management
    • Statistical Analysis for Health Data Insights

     

    Elective Subjects# (0 to 2 subjects*, 3 credits each) 

    • AI in Medical Imaging
    • Anatomy and Physiology
    • ESG in Healthcare
    • Health Analytics for Public Health Surveillance
    • Preventive Care and Health Promotion
    • Sports Nutrition and Performance

     

    ^ Applicable to students from non-computer-science-related disciplines only.

    @ Applicable to students from non-health-science-related disciplines only.

    Offering of any elective subjects is subject to sufficient enrolment.

    For students from both non-computer-science-related disciplines and non-health-science-related disciplines, they are required to complete both the compulsory subjects “Low-code to No-code AI Solutions” and “IoT and Wearables for AI-driven Healthcare”.  No elective is required for them.  For students either from non-computer-science-related disciplines or non-health-science-related disciplines, they are required to complete the compulsory subject “Low-code to No-code AI Solutions” or “IoT and Wearables for AI-driven Healthcare” respectively and will need to take one elective only.  Other students will need to take two electives.

    ** Individual students who have not fulfilled the English language requirements before admission are required to take an additional Adjunct English subject (3 credits). Please refer to the “Entrance Requirements” section for details. The additional credit / subject requirements will be reflected on the “My Graduation Requirements” accessible from the Student Portal as the programme commencement approaches.  Students concerned are required to pay additional fees after programme commencement.

    Entrance Requirement

    Holders of a recognised bachelor’s degree, or an equivalent qualification in computer science, statistics, health information sciences, health sciences, or a related disciplines.


    Notes: 

    1. An applicant who is not a native speaker of English, and does not possess a Bachelor’s degree or an equivalent qualification for which English was the primary medium of instruction, is expected to fulfil the following minimum English language requirements:
      1. An overall Band Score of 6.0 in the International English Language Testing System (IELTS); OR
      2. A Test of English as a Foreign Language (TOEFL) score of 80 for the Internet-based test or 550 for the paper-based test; OR
      3. Satisfactory results in other recognised English language assessments

    Individual cases may be considered on their own merit, and applicants concerned may be required to take an additional 3-credit Adjunct English subject upon admission.

    1. An applicant who does not possess the above-mentioned qualifications but has reached the age of 25 before 1 September, in the academic year in which he/ she seeks admission, may apply as a mature applicant.  He/ she must demonstrate sufficient motivation, knowledge and potential to indicate a high probability of being able to complete the programme successfully.

    Enquiries

    Academic Matters:Dr CHEUNG, Tsuen-yuen Simon
    Senior Lecturer I and Senior Continuing Education Consultant, 
    BSc (Br.Col.), MSc (C.U.H.K.), EdD (Brist.);FACHSM, FHKCHSE

    3746 0079

     
    General Administrative Matters:CPCE Academic Registry 

    3746 0900