Image of heart with heart rhythm and data code.

Transforming Hypertension Diagnosis and Management in the Era of Artificial Intelligence

March 29 - 30, 2023
Virtual Workshop
11 a.m. - 4 p.m. EDT


High blood pressure, known as hypertension, is still a significant health problem worldwide. To better diagnose and manage the disease, healthcare providers need more reliable and exact measurements. Machine learning or artificial intelligence tools could offer better ways to improve current approaches for the detection, monitoring, and management of hypertension.

Join the National Heart, Lung, and Blood Institute for a virtual workshop that brings together health care providers and researchers with expertise in hypertension along with data scientists, engineers, and implementation scientists. Participants will explore data integration strategies, novel technologies, and innovative analytical methods, with the goal of finding ways to improve hypertension detection, monitoring, and management.

The workshop features panel discussions on:

  • Bridging the communication gap between population health, clinical medicine, and engineering
  • Improving blood pressure measurement and control and reducing hypertension risk
  • Using artificial intelligence to predict, monitor, and treat hypertension
  • Addressing real world implementation challenges and issues

Other topics include health disparities, novel technologies, data harmonization, electronic health records, clinical decision tools, medication adherence, and clinical and regulatory issues. The workshop also features a keynote presentation on real-world challenges for communities most impacted by hypertension.

This workshop is open to the public and will be recorded. View registration details.


View the current agenda.


Watch via NIH videocast:
Day 1:
Day 2:


Register Now:


Individuals with disabilities who need sign language interpreters and/or reasonable accommodation to participate should contact the NHLBI Workshop Support team at least five days prior to the event.


For logistical questions, email Alexandra Guillermety. For programmatic questions, email Erin Iturriaga.

Select Speakers

Rashmee Shah
University of Utah School of Medicine
Dr. Rashmee Shah is an assistant professor in cardiovascular medicine at the University of Utah School of Medicine. Her research focuses on clinical applications of data science, machine learning, and natural language processing.
Rashmee Shah, M.D., M.S.
Daichi Shimbo
Columbia University Irving Medical Center
Dr. Daichi Shimbo is a cardiologist and professor of medicine at Columbia University Irving Medical Center. He is also co-director of the Columbia Hypertension Center. His clinical interests include the correct diagnosis and treatment of hypertension.
Daichi Shimbo, M.D.
Erica Spatz
Yale School of Medicine
Dr. Erica Spatz is a general cardiologist and a clinical investigator at the Center for Outcomes Research and Evaluation (CORE) in the Yale School of Medicine. Her clinical and research interests include developing individualized approaches to prevent and manage cardiovascular disease.
Erica Spatz, M.D., M.H.S.