Cardiovascular Analytic Intelligence Initiative

Cardiovascular Analytic Intelligence Initiative (CV-Ai2) aims to find new and innovative ways to better utilize the data generated through clinical activity to design solutions that help solve important clinical problems. These solutions are then deployed in the hospital setting and directly evaluated at the physician and patient level.

In This Section:

Our Vision | Our Team | Showcase Projects | Student Opportunities | Contact Us

Our Vision


We develop the infrastructure necessary for real-time acquisition and utilization of clinical data in predictive models. This includes developing the technology for real-time data extraction and processing and integration of predictive models into the clinical IT infrastructure.

From Analytics to Analytic Intelligence

Among the hundreds of predictive models developed for cardiovascular disease, only <0.1% actually end up routinely used in clinical practice. The Cardiovascular Analytic Intelligence Initiative (CV-Ai2) was created at Johns Hopkins University to specifically address this translational crisis. The key to address the current limitations of predictive models will be to move beyond data analytics and artificial intelligence and focus on analytic intelligence. Analytic intelligence is a multi-step process in which predictive models are created while considering the full requirements for their deployment and evaluation, which is an intrinsic part of the process. The move to analytic intelligence will be necessary to fully realize the potential of machine learning and artificial intelligence in clinical settings.

Predictive Models

We develop and test new strategies to create predictive models for clinical use using best-in-breed biostatistical methods and machine learning. Our focus is on methods that allow for the utilization of complex and deep data without using data reduction methods.

Our Team

  • Vivek Jani, M.S., Medical Student
  • Joseph Shin, B.S., Medical Student
  • Junzhen Zhan, M.D., Ph.D., Research Fellow

Showcase Projects

Student Opportunities

We offer a variety of opportunities for students in medicine, public health, data sciences and computer sciences to contribute to research projects. There are many ways to contribute to projects and previous coding or data analytics experience is not necessary for all projects. The only prerequisite is previous completion of a biostatistics course at the undergraduate level.

Students typically dedicate at least 4–6 hours per week on projects with flexible schedule. Students who provide substantial contributions on a project will be invited to lead manuscript preparation and presentation of results at national and international conferences.

Positions for graduate students and post-doctoral fellows will be available starting the second half of 2020. Details to come.

Contact Us

For CV-Ai2’s vision to become a reality, our academic, clinical and industry partners must come together and work toward a common goal. CV-Ai2 is grateful for the partners who help make our vision possible, and we are always looking for more collaborators. If you share our vision and want to get involved, please do not hesitate to contact us at [email protected].