Researcher looking at biological data on a monitor.

Health Informatics—MS

Michigan Tech's MS in Health Informatics offers a flexible, challenging curriculum that can be completed both on-campus and entirely online. The program utilizes a robust cloud-based computing environment, allowing students to access a secure virtual lab remotely from any web browser to conduct applied hands-on labs and develop advanced skills in health informatics and biomedical data science.

Health informatics, a multi-disciplinary professional field, studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem-solving, and decision making. The advancement of technology in the medical field, accompanied by the requirements to keep sensitive data confidential, has created a robust need for health informatics specialists who work at he intersection of information science, computer science, and health care.

Research Focus

Deep-learning algorithms to improve differentiation of breast abnormalities in mammography images. Health identifiers to prevent patient misidentification, enhance data security, improve patient safety, and lower health care costs. Research in labs dedicated to developing new, more effective techniques and technologies that forge new pathways to secure and comprehensive information for every member of the health care community.

An interdisciplinary approach to research, focusing on innovations that benefit society and the environment brings students and faculty together at the Institute of Computing and Cybersystems and Health Research Institute. CyberS, the Center for Cybersecurity, expands innovation in the field most crucial to Information Technology, from information security and biometrics to trusted software engineering. DataS, the Center for Data Sciences, unites diverse faculty and students to discover new knowledge in interdisciplinary collaboration. At the Center for Human-Centered Computing, Michigan Tech students learn to become future creators, finding the balance of computing, humanity, and interaction.

Stackable Graduate Certificates

The curriculum is structured around four graduate certificates, beginning with the 12-credit Foundations of Health Informatics certificate, which covers core courses in the health informatics field. Students then choose two of three additional 9-credit "stackable" certificates in specialized areas: Artificial Intelligence in Healthcare, Security and Privacy in Healthcare, and Public Health Informatics. With a minimum of 30 credits required for the MS degree, most students graduate with both the master's degree and three graduate certificates.

MS Requirements

Health Informatics Graduate Foundations Courses (12 credits)
Focus Areas (9-18 credits)
Elective courses or Report option or Thesis option (6-10 credits)

Graduate Handbook

Elective Courses

A maximum of two courses or six credits may be used for elective credit.
Any SAT 5000 level course not taken from above and the following.

UN 5550 - Introduction to Data Science

Introduces concepts and skills fundamental to Data Science including: getting data, data wrangling, exploratory data analysis, basic statistics, data visualization, data modeling, and learning. The course introduces data science from different perspectives: computer science, mathematics, business, engineering, and more.

Credits: 3.0
Lec-Rec-Lab: (2-0-2)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Data Science

MA 5790 - Predictive Modeling

Application, construction, and evaluation of statistical models used for prediction and classification. Topics include data pre-processing, over-fitting and model tuning, linear and nonlinear regression models and linear and nonlinear classification models.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Fall, Spring
Pre-Requisite(s): MA 3740 or MA 4710 or MA 4720 or MA 4780 or (MA 4700 and MA 5701)

BA 5200 - Information Systems Management and Data Analytics

Focuses on management of IS/IT within the business environment. Topics include IT infrastructure and architecture, organizational impact of innovation, change management, human-machine interaction, and contemporary management issues involving data analytics. Class format includes lecture, group discussion, and integrative case studies.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Accounting, Data Science, Engineering Management, Applied Natural Resource Econ., Health Informatics, Accounting and Analytics, Business Administration

FW 5083 - Programming Skills for Bioinformatics

Students will learn computer programming skills in Perl for processing genomic sequences and gene expression data and become familiar with various bioinformatics resources.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, in odd years
Restrictions: Must be enrolled in one of the following Level(s): Graduate

MA 5781 - Time Series Analysis and Forecasting

Statistical modeling and inference for analyzing experimental data that have been observed at different points in time. Topics include models for stationary and non stationary time series, model specification, parametric estimation, model diagnostics and forecasting, seasonal models and time series regression models.

Credits: 3.0
Lec-Rec-Lab: (0-3-0)
Semesters Offered: Spring
Pre-Requisite(s): (MA 2710 or MA 2720 or MA 3710 or MA 3715 or MA 5701) and (MA 3720 or EE 3180 or MA 4700)

KIP 4740 - Epidemiology

An introduction to the principles and methods of epidemiology to understand the distribution and determinants of health in a population. Topics include basic epidemiological statistics, study design, and sources/impact of bias and error.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Spring

EET 4501 - Applied Machine Learning

Introduces the general concepts and algorithms of machine learning (ML) with their implementation and applications to practical problems of modeling, detection, estimation, prediction, and control. Applications include cybersecurity, healthcare, robot vision, remote sensing, automation, and natural language processing.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Spring
Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore
Pre-Requisite(s): SAT 4310 or SAT 4650 or CS 1121

Degree Options

The program offers research, thesis, and reporting options for both on-campus and online students, and openly encourages those completing the "coursework only" option to participate in faculty research projects. Graduates of the program are well-prepared for careers as biomedical data scientists, clinical EHR integration specialists, clinical data analysts, and other in-demand roles in the healthcare sector.

MS, Health Informatics: Thesis Option

This option requires a research thesis prepared under the supervision of the advisor. The thesis describes a research investigation and its results. The scope of the research topic for the thesis should be defined in such a way that a full-time student could complete the requirements for a master’s degree in 12 months or three semesters following the completion of coursework by regularly scheduling graduate research credits.

The minimum requirements are as follows:

Total Credit Requirements
Option Parts	Credits
Coursework (minimum)	20 Credits
Thesis research	6-10 Credits
Total (minimum)	30 Credits

Distribution of Coursework Credit
Distribution	Credits
5000-6000 series (minimum)	12 Credits
3000-4000 (maximum)	12 Credits

Programs may have stricter requirements and may require more than the minimum number of credits listed here.

MS, Health Informatics: Report Option

This option requires a report describing the results of an independent study project. The scope of the research topic should be defined in such a way that a full-time student could complete the requirements for a master’s degree in twelve months or three semesters following the completion of coursework by regularly scheduling graduate research credits.

Of the minimum total of 30 credits, at least 24 must be earned in coursework other than the project:

Total Credit Requirements
Option Parts	Credits
Coursework (minimum)	24 Credits
Report	2-6 Credits
Total (minimum)	30 Credits

Distribution of Coursework Credit
Distribution	Credits
5000-6000 series (minimum)	12 Credits
3000-4000 (maximum)	12 Credits

Programs may have stricter requirements and may require more than the minimum number of credits listed here.

MS, Health Informatics: Coursework Option

This option requires a minimum of 30 credits be earned through coursework. A limited number of research credits may be used with the approval of the advisor, department, and Graduate School. See degree requirements for more information.

A graduate program may require an oral or written examination before conferring the degree and may require more than the minimum credits listed here:

Distribution of Coursework Credit
Distribution	Credits
5000-6000 series (minimum)	18 Credits
3000-4000 (maximum)	12 Credits

Application Process and Admissions Requirements

Applications are reviewed on an individual basis using a holistic approach. Fill out our free graduate application online to apply to any of our programs. Official transcripts and scores are not required for the initial application, although you will need to upload them later.

Graduate School Admissions Process

Applying to Graduate School is free (no application fees) and fast (no official transcripts or test scores are needed to start). The application process involves three easy steps. International applicants are required to pay a non-refundable $10 processing fee per application.

See Admissions Steps

Graduate School Admissions Options

Michigan Tech offers several admissions options in order to meet the educational needs of students from a variety of backgrounds. Students should review the options available to them and apply for the program that will best help them achieve their personal educational goals.

See Admissions Options

Graduate School Requirements

To be considered for admission to the Graduate School as a degree- or certificate-seeking student, you need to:

have a bachelor's degree or its equivalent from an accredited institution, and
be prepared for advanced study in your chosen field, as demonstrated by your previous degree and your scholastic record.

See additional application requirements, including required materials:

Student Statements

Official Transcripts

Program Specific Requirements

Program Specific

3 Letters of Recommendation
Résumé / Curriculum vitae
Admitted applicants typically have an undergraduate GPA of 3.0 or better on a 4.0 scale
No GRE Required

International Students

TOEFL: Recommended Score of 79 iBT
IELTS: Recommended Overall Band Score of 6.5

Michigan Tech requires a minimum 79 overall TOEFL or 6.5 overall IELTS score.

Admissions Decisions

Made on a rolling basis.

Recommended Deadline

Apply at least a semester in advance of projected admission to improve your chances of receiving funding.

International Student Requirements

International Students must apply and be accepted into a degree-granting program in order to earn a graduate certificate. A non-refundable $10 processing fee per application is required.

See International Applicants

Accelerated Master's Requirements

Our Accelerated Master's Program is available for current Michigan Tech students.

Program Specific

3 Letters of Recommendation
Overall GPA of 3.0 or greater
No GRE required

Eligible Undergraduate Majors

Computer Network and System Administration

Accredited by HLC

Michigan Tech has been accredited by the Higher Learning Commission (HLC) since 1928. Our Graduate School offers over 125 certificates, master's, and PhD programs to provide our students and the world with what tomorrow needs.

Funding Opportunities

Decisions on financial support and contract offers for the upcoming academic year are typically made in the spring semester. Financial support is not guaranteed. Applicants for GRA (Graduate Research Assistant) positions should submit a current vita emphasizing their research qualifications.

Financial Aid Resources

Graduate students have many University-related aid options available to them. The Financial Aid Office provides an extensive list of resources to aid students in finding additional funding opportunities.

Cost of Education

Helpful cost of education links for students on fellowship, who qualify for educational tax credits, or who are nonresidents.

Tax Information (Residents | Nonresidents)

Learn about important tax information for resident and nonresident graduate students.

Fellowships and Scholarships

Resources

Health Information Management System Society (HIMSS)

The Health Information Management System Society are leaders in health innovation, public policy, workforce development, research, and digital health transformation to advise leaders, stakeholders, and influencers from across the global health ecosystem on best practices. Free Membership to MTU Health Informatics Students!

Advantages of being a HIMSS Member:

Network with your peers
Access informative content
Develop leadership experience
Save money
Stay informed

LEAP Advantage

Students from India, earn your STEM master’s degree at one of the leading health informatics departments in the US with state-of-the-art labs and computer centers.

GRE scores are waived for students applying through Leap Advantage.
1st semester, study online in India and then transition to Michigan Tech’s campus.
Academic mentoring, pedagogy, and coursework by MTU faculty and staff.
Non-academic support provided by Leap, including visa, counseling, mentorship, and soft skills training.
Save on overall costs and still have OPT opportunities.

Eligibility

An undergraduate degree in a health related or computing focused field from a regionally accredited academic institution with a cumulative GPA of 3.00 or higher on a 4.0 scale.

Learn More

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