Master in Artificial Intelligence and Health Informatics (MAIHI)

Plan of Study Master in AI and Health Informatics (MAIHI)

Total Credit Requirements: 33 Credits

Course Description

Year 1: Semester 1

MAIHI 600, AI in Healthcare (Preparatory)

This course is designed to develop the basic understanding in the healthcare and information technology required for the Master in AI and Health Informatics program. In this preparatory course a student will get a sense of how AI could transform patient care and diagnoses. The course will also include the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically.  This preparatory course is designed for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines.

MAIHI 601, Healthcare System Science

This course offers a comprehensive introduction to Health Systems Science, a critical field that bridges the gap between clinical care and the systems within which healthcare operates. Students will explore the structures, processes, and dynamics of health systems, gaining insights into how healthcare is delivered and how professionals collaborate to improve patient outcomes. This course aims to develop foundational skills in teamwork and leadership within health contexts, preparing students to contribute effectively to health systems transformation.

MAIHI  602, Research Methodology for Health Informatics

Research Methodology for Health Informatics equips students with the foundational skills to design, conduct, and evaluate research in health informatics. The course covers research design, data collection techniques, statistical analysis, and ethical considerations, emphasizing the application of evidence-based methods to address challenges in healthcare technology and informatics.

MAIHI 603, Python Programming for Decision Science

This course introduces the fundamentals of Python programming tailored for decision science applications. Decision science encompasses various disciplines such as operations research, management science, and data analytics, focusing on making data-driven decisions to optimize outcomes. Python, with its extensive libraries and easy-to-learn syntax, is a powerful tool for implementing decision science methodologies. Throughout the course, students will learn Python programming concepts and techniques essential for decision science tasks.

Year 1: Semester 2

MAIHI 604, Ethical Considerations in Health Informatics

This course dives deep into the critical areas of ethics, privacy, and security surrounding healthcare data. You’ll explore the ethical considerations that shape healthcare practices and gain a solid understanding of information management principles and how to safeguard patient privacy. The course also weaves in advanced security measures, keeping you up to date on the latest threats and risk assessments. By leveraging complex security theories, you’ll gain a clear understanding of regulations like HIPAA and FIPP.

MAIHI 605, Application of Artificial Intelligence in Healthcare

This course unlocks the potential of Artificial Intelligence (AI) in healthcare. Dive into the world of AI technologies and discover how they’re revolutionizing various aspects of medicine, from diagnosing diseases to developing life-saving drugs. Explore the impact of AI on medical devices, healthcare facilities, patients, administrators, and providers alike. Through a blend of engaging lectures, hands-on exercises, and real-world case studies, you’ll gain the skills to interpret medical data using cutting-edge AI techniques. This course equips you to be a part of the future of healthcare, where AI plays a transformative role.

MAIHI 606, Machine Learning and Predictive Analytics in Healthcare and Big Data

This course provides an in-depth exploration of machine learning techniques and predictive analytics in the context of healthcare. It equips students with the knowledge and skills necessary to leverage data-driven approaches to improve patient outcomes, optimize healthcare operations, and enhance decision-making processes within healthcare systems.

MAIHI 607, Deep Learning Applications in Healthcare

This course empowers you to unlock the power of deep learning in healthcare. We’ll delve into the foundational concepts of deep learning, specifically tailored to the healthcare industry. Through a blend of theory and practice, you’ll gain the skills and knowledge to tackle complex healthcare data. You’ll master various deep learning techniques, tools, and methodologies used by healthcare professionals to solve real-world problems.

Year 1: Summer Semester

MAIHI 608, NLP and Gen AI in Healthcare

This course introduces students to the concepts and applications of Natural Language Processing (NLP) and Generative Artificial Intelligence (AI) in the healthcare domain. Students will learn the fundamental principles of NLP and Generative AI and explore their specific applications and challenges in healthcare settings. Through a combination of lectures, hands-on exercises, and real-world case studies, students will gain practical skills in leveraging NLP and Generative AI techniques to analyze medical texts, extract valuable information from unstructured data, and generate meaningful insights to support clinical decision-making and improve patient care.

MAIHI 610A, Thesis in AI and Health Informatics -I

The Thesis in AI and Health Informatics – I, is a foundational course designed to guide students in identifying and preparing a research project that aligns with the program’s focus on advancing healthcare through AI-driven innovations. This phase emphasizes the selection of a meaningful research topic, understanding the current state-of-the-art in the chosen area, developing a robust data strategy, and establishing a structured plan for research execution under expert supervision.

Year 2: Semester 3

MAIHI 609, Leadership, Strategy and Change Management

This course provides students with a comprehensive understanding of the principles and practices of leadership, strategy development, and change management in organizations. Through a combination of theoretical concepts, case studies, and practical exercises, students will explore the interrelationships between leadership, strategy formulation, implementation, and organizational change. Topics covered include leadership styles and theories, strategic planning processes, organizational culture, innovation, and managing resistance to change. Students will develop critical thinking skills and practical strategies for leading and managing organizational change initiatives effectively.

MAIHI 610 B, Thesis in AI and Health Informatics-II

The Thesis in AI and Health Informatics – II is the execution phase of the research project, where students apply their knowledge and skills to solve real-world healthcare challenges using AI. This course focuses on implementing the approved thesis proposal, including research methodology, data collection, model development, and presenting findings.

Applicants for the Master in AI and Health Informatics on an individual basis. A combination of factors is considered based on the applicant’s profile including:

• Applicants shall meet all admission criteria for entry into the higher education programs offered by the University, as laid down in the Standards (2019) for Licensure and Accreditation published by Commission for Academic Accreditation, the Ministry of Education (MOE) – Higher Education Affairs.
• Applicants for the Master in AI and Health Informatics shall have a recognized Baccalaureate degree earned in a discipline appropriate for the prospective graduate degree with a minimum cumulative grade point average of 3.0 on a 4.0 scale or its established equivalent.
• The Applicant must have proficiency in spoken and written English. The applicant can fulfil the English proficiency requirement via the TOEFL, IELTS, or UA CESL Endorsement Exam, minimum requirements are listed below. TOEFL and IELTS test scores must be dated within two years of the year of enrolment.
  • EmSAT: Score of 1400 and above
  • TOEFL: Score of 79 on the iBT or 550 PBT (web-based) test or higher.
  • IELTS: Overall score of 6 is required, with a score of no less than 5 on any individual band or module.

Conditional Graduate Admission Read More

Letter of Motivation and Interview

Applicants meeting the general requirements for the program will be required to submit a letter of motivation and attend a personal interview. Based on the evaluation, applicants may be advised to complete a preparatory course “AI in Healthcare Specialization” from Standford University available through the Coursera Platform.

Graduation Requirements & Competencies

The student will be recommended for the award of the degree of Master in AI and Health Informatics.

• Completion of 33 credits
• Obtaining a minimum CGPA of 3.0
• Obtaining a Cumulative Grade B or above
• Submitting and defending a thesis work to the satisfaction of the project evaluation committee with a minimum pass mark of 80%
• Securing a minimum attendance of 80%

Competencies Developed from the Program include but not limited to:

• Understanding Healthcare Systems: Graduates will gain a deep understanding of healthcare system foundations, including their structure, functions, and key challenges, enabling them to navigate and address complex issues in healthcare.
• Ethical Decision-Making: Graduates will be equipped to identify and apply ethical principles, frameworks, and guidelines in health informatics, ensuring responsible and ethical use of technology in healthcare.
• Data Science Expertise: Graduates will develop proficiency in applying data science and big data analytics techniques to solve real-world healthcare challenges, leveraging data to improve decision-making and outcomes.
• AI and Predictive Analytics Skills: Graduates will acquire advanced skills in analyzing healthcare data using artificial intelligence, machine learning models, and predictive analytics to derive actionable insights and drive innovation.
• Leadership in Health Informatics: Graduates will demonstrate strong leadership capabilities, including strategy development and change management, to effectively lead projects and teams in the AI and health informatics domain.
• Research and Problem-Solving: Graduates will be capable of conducting field research on identified healthcare problems, utilizing AI and health informatics tools to develop innovative, evidence-based solutions.

Apply Now: [link]

Graduates of this program can pursue diverse and rewarding careers at the intersection of healthcare and technology. Graduates may find employment opportunities in hospitals, healthcare systems, technology companies, research institutions, consulting firms, and government agencies. Potential roles include:

• Health Informatics Specialist: Managing and analyzing healthcare data to improve clinical workflows and patient outcomes.
• AI Solutions Architect for Healthcare: Designing and implementing AI-driven solutions tailored to healthcare challenges.
• Data Scientist in Healthcare: Applying data science techniques to solve healthcare problems, from predictive analytics to population health management.
• Clinical Data Analyst: Analyzing clinical data to support evidence-based decision-making and operational efficiency.
• Digital Health Consultant: Advising healthcare organizations on the adoption and optimization of digital technologies, including AI.
• Healthcare AI Researcher: Conducting research on AI applications in healthcare, including diagnostics, treatment optimization, and patient monitoring.
• Health IT Project Manager: Leading the development and implementation of health IT projects, ensuring alignment with organizational goals.
• Ethics and Compliance Officer in Health Informatics: Overseeing ethical considerations and regulatory compliance in AI and health informatics initiatives.
• Healthcare Quality Improvement Analyst: Utilizing data-driven insights and AI tools to enhance the quality and safety of healthcare delivery.
• Entrepreneur in Digital Health: Developing innovative AI and health informatics solutions to address unmet needs in the healthcare industry.