Artificial Intelligence in Cardiovascular Disease Fellowship
We have launched a first-of-its-kind fellowship to mentor the next generation of clinicians in the use of artificial intelligence (AI) in cardiovascular medicine. This one-year training program will involve experienced faculty members from both Northwestern Medicine Bluhm Cardiovascular Institute and Northwestern University McCormick School of Engineering and will be geared toward cardiology, cardiac surgery and internal medicine trainees.
About the Fellowship
The program begins with one quarter of intensive immersion in computation, programming and statistics that serves as the foundation for learning more advanced computational approaches. The subsequent three-quarter sequence in AI, machine learning (ML) and data science will focus on the knowledge and skills needed to address the exploration and use of AI and ML systems in the development of new healthcare solutions.
The curriculum for this sequence will include classes in human-computer interaction (HCI) and the elements of human cognition considered when building intelligent systems. This integrated research program occurs in parallel with the advanced classes where students do computationally enabled research advised by faculty in heart disease and computer science. Research opportunities alongside senior faculty members will help shape the trainees' experiences, preparing them for successful careers.
Example Projects
Fellows in the inaugural year of this fellowship worked on numerous projects that will advance the field of cardiovascular medicine and pave the way for AI-assisted diagnosis and treatment, including:
- Training computer algorithms to recognize and diagnose types and locations of cardiac arrhythmias from the 12 lead ECG
- Automating the identification of new serum markers, image characteristics and patient characteristics for those with cardiovascular complications related to kidney disease
- Using computer vision technology to automatically interpret cardiac nuclear imaging for the early detection of cardiac amyloidosis
- NLP to derive structured data from medical notes in electronic health records/MRI/echo reports
- Developed "Deep COVID-XR," an AI system for detecting COVID-19 on chest X-ray (published in Radiology, November 2020)
Eligibility
Successful candidates will hold a graduate doctoral degree (MD, DO) prior to beginning the fellowship and a current, valid medical license (non-restricted).
Applicants currently in clinical programs should expect that most of their time will be devoted to classwork and should arrange to apply during their research year.
Application Process
Interested candidates should send the following materials to bcvi.msai@nm.org for review by our selection committee:
- Letter of interest
- Current curriculum vitae
- Three letters of recommendation
- One from current (or most recent) ACGME program director
- Two from faculty familiar with your work clinically or academically
Qualified fellows will be invited to submit further materials.
Contact Us
Please direct inquiries regarding the application process — or the non-clinical, non-ACGME, computer science fellowship in AI — to BCVI.MSAI@nm.org.