Artificial Intelligence in Healthcare (AIHC) – Certificate
- David Holmes III, Ph.D, Program Director
The Certificate track in Artificial Intelligence in Health Care is open only to Mayo Clinic employees who have a doctoral degree in a discipline applicable to research. Doctoral candidates may be considered. Potential candidates for the degree must hold Mayo Clinic appointments of sufficient duration to complete the program requirements.
Pre-Requisite Course Work
- Introduction to statistics: Data summarization and statistical testing (like CTSC 5600)
- Linear Algebra: Matrix Math
- Calculus: Single variable (“Calc 1”)
- Introduction to Scientific Programming (Python and/or R preferred)
Application
Candidates must complete a Certificate Application form. This form is available on the MCGSBS Certificate Programs intranet site. Supporting documents include a program fee agreement form, letter of recommendation (from a person who is acquainted with your personal, academic, or professional qualifications) and CV/Resume. Applicants must be approved by the track program director and admission endorsed by MCGSBS.
Eligibility
Applicants must be employed at Mayo Clinic. The employment appointment, as documented at the time of application, must be greater in length than the time required for completion of all requirements of the program. Eligible roles include: Mayo Clinic physician, scientist, fellow or resident with a doctoral degree in a discipline applicable to research or medical student who plans to have a research career.
Time Requirement
Applicants must have adequate protected time to complete course requirements within designated program length. Students must abide by course attendance requirements as defined in course syllabi.
Minimum Credit Requirements
Students must complete a minimum of 12 credits.
Transfer Credits
A total of 3 didactic credits may be transferred into the certificate program. For more details, see the Credit Conversion, Transfer, Waiver, and Substitution Policy on the MCGSBS Policies and Procedures intranet site.
Course Work
The curriculum for the Certificate consists of 12 credits. The student must complete all of the required courses listed below:
| Code | Title | Hours |
|---|---|---|
| Course Requirements | ||
| AIHC 5020 | Introduction to Data | 3 |
| AIHC 5030 | Introduction to Deployment, Adoption & Maintenance of Artificial Intelligence Models/Algorithms | 2 |
| CTSC 5300 | Foundations of Epidemiology | 1 |
| CTSC 5350 | Ethical Issues in Artificial Intelligence and Information Technologies | 1 |
| AIHC 6000 | Independent Study in Artificial Intelligence in Healthcare | 1 |
| Total Hours | 8 | |
| Code | Title | Hours |
|---|---|---|
| Electives | 4 | |
Select one of the following: | ||
| Introduction to Machine Learning | ||
| AI Fundamentals for Healthcare Professionals | ||
| Deep Learning for Medical Imaging | ||
| Applied Data Science and Artificial Intelligence in Pharmacology | ||
Select one of the following: | ||
| Fundamentals of Statistics for Artificial Intelligence | ||
| Statistics in CTR: Linear Regression Concepts, Interpretation, and Statistical Software | ||
| Total Hours | 4 | |
Independent Study
The independent study is an opportunity to demonstrate the integration of knowledge from the concentration courses. Through the independent study with one of the faculty of the AIHC track, the learning will complete a project or writeup related to the use of AI in their scientific domain. The faculty and learner will meet at the beginning of the term to define the specific learning objectives and academic output from the Independent Study.
Cost
A program fee is charged for Certificate programs to cover administrative costs, due upon admission. The cost is covered by Mayo Clinic funds, either by the candidate’s home department or lab, or by the Mayo Clinic’s Career Investment Program (CIP) if eligible and selected by CIP.
Suggested Sequence
This is a suggested sequence based on a summer term start. Individual course plans may vary depending on true start date, program, employment/personal commitments, and research interests. Note that Certificate learners will choose between groups of courses to complete the certificate requirements. Be sure to confirm you have met your requirements using your degree planning tool. Course offerings may vary slightly. Current course offerings are posted in the course catalog.
| Code | Title | Hours |
|---|---|---|
| First Year - Summer Term | ||
| AIHC 5020 | Introduction to Data | 3 |
| Code | Title | Hours |
|---|---|---|
| First Year - Fall Term | ||
| AIHC 5100 | AI Fundamentals for Healthcare Professionals | 2 |
| AIHC 5615 | Fundamentals of Statistics for Artificial Intelligence | 2 |
| CTSC 5300 | Foundations of Epidemiology | 1 |
| CTSC 5610 | Statistics in CTR: Linear Regression Concepts, Interpretation, and Statistical Software | 3 |
| MPET 6450 | Applied Data Science and Artificial Intelligence in Pharmacology | 2 |
| Code | Title | Hours |
|---|---|---|
| First Year - Winter Term | ||
| AIHC 5010 | Introduction to Machine Learning | 3 |
| CTSC 5350 | Ethical Issues in Artificial Intelligence and Information Technologies | 1 |
| Code | Title | Hours |
|---|---|---|
| First Year - Spring Term | ||
| AIHC 6000 | Independent Study in Artificial Intelligence in Healthcare | 1-3 |
| AIHC 5030 | Introduction to Deployment, Adoption & Maintenance of Artificial Intelligence Models/Algorithms | 2 |
| BME 6720 | Deep Learning for Medical Imaging | 3 |