
11 a.m. - 4 p.m. EDT
Description
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.
Agenda
Videocast
Watch via NIH videocast:
Day 1: https://videocast.nih.gov/watch=49303
Day 2: https://videocast.nih.gov/watch=49305
Register
Register Now: http://bit.ly/3HCtLBJ
Accommodations
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.
Contact
For logistical questions, email Alexandra Guillermety. For programmatic questions, email Erin Iturriaga.