The AI in Digital Health certificate program provides a comprehensive and in-depth education on the intersection of artificial intelligence and healthcare. With a focus on practical applications and real-world examples, students will gain the knowledge and skills needed to excel in this growing field.
Who should apply for the Graduate Certificate in AI in Digital Health?
The program is designed for students with computer science backgrounds who want to learn AI applications in healthcare, and students with biomedicine backgrounds or health professionals who want to learn AI technology.
- Understand how data are generated, collected, and annotated in each individual healthcare research field.
- Use existing or develop new AI/ML models for healthcare data analytics.
- Effectively communicate and disseminate knowledge in any science or engineering domain in the context of computing, systems, and/or biomedical applications.
The program is a total of four courses (12 credit hours). There is one required course and the student can then choose three elective courses from six possible options. Students will take one to two online courses each semester, in-person courses cannot be substituted. This program can be completed in as few as 2 semesters.
BMI 5780 - Programming for Biomedical Informatics
This course provides foundational and practical knowledge, skills, and tools for programming in Biomedical Informatics, a field that utilizes complex and diverse data. Multiple programming languages and software tools are used to work with these data and new ones are continuously developed. Upon completing the course, students will have acquired the necessary programming knowledge and skills to program in Python and implement popular data analysis methods and machine learning algorithms for Biomedical Informatics research.
- BMI 5551 – Survey of AL/ML in Digital Health - Students will interact with ML/AI technologies to create novel innovations in biomedical and clinical research and healthcare.
- BMI 5552 – AI/ML Applications in Medical Imaging - Students gain an introductory knowledge of how AI can be used in medical image processing applications.
- BMI 5553 Predictive Analytics in Electronic Health Records - As EHR databases are becoming more standardized and integrated across multiple hospital systems, they are gaining increasing attention from the informatics community as a resource to be mined, for example, to assess quality of patient care, develop early prediction models for disease, and define disease phenotypes.
- BMI 5554 Natural Language Processing in Biomedical Informatics - This course introduces trainees to the natural language processing and text mining on biomedical data, including clinical notes from electronic medical records and biomedical literature.
- BMI 5750 Methods in Biomedical Informatics and Data Science – This course educates trainees in practical biomedical informatics, study design, statistical analysis, and computational techniques related to biomedical research.
- BMI 7235 Applications of Machine Learning for Bioinformatics -- This course will teach students the primary machine learning algorithms used in bioinformatics.
A background in the basic sciences, medicine, or computational sciences is preferred. If you are interested in pursuing a certificate but are worried you might not meet the qualifications, please contact us at BMI.Education@osumc.edu to see which options might be available for you.
How To ApplyThe annual application deadline is July 31st. A bachelor’s degree is required for all certificates. Applicants must submit:
- Completed online application (fee included)
- College transcript
- Personal statement
- Current resume or CV
Applications for the AI in Digital Health certificate will open in Spring 2024! Check back here for the application link.