Upcoming Events
Exploring the Transformative Impact of Applied AI on Healthcare Workshop
Explore how AI, augmented by human insight, can profoundly improve health outcomes.
April 23, 2024, 8:30 AM – 2:15 PM
Center for Academic Excellence, Ochsner Main Campus, Classrooms 1- 3, 1401-A Jefferson Highway, 1st Floor, New Orleans, LA 70121
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Participants
Academic Institutions:
- University of Louisiana at Lafayette
- Tulane University
- Georgia Tech
- LSU Health Sciences Center, New Orleans
- University of Florida
State Agencies:
- Louisiana Department of Health
Industry:
- Ochsner Health
- CGI
- Aetna
- Haltian Inc
- OneTeleMed (Telemedicine)
Workshop Goals & Objectives
Despite the highest healthcare spending, the U.S. has poorer health outcomes compared to other high-income countries, with Louisiana ranking low on many health indicators ranging from chronic diseases to behavioral health. AI holds the promise of enabling quicker and better-informed decision-making for patients, doctors, and policymakers, and can enhance health behaviors by better managing individual to population health.
The goal of the workshop is to bring in interdisciplinary experts (e.g., physicians, health policy experts, public health scholars, and AI researchers) to help understand challenges posed by fragmented information infrastructure from multiple perspectives, gaps in patient behavior sensing, and how these issues affect health outcomes. The workshop will foster collaboration between AI researchers and health experts to jointly identify challenge areas, sources of funding, and collaborative research opportunities.
Objectives: The workshop is structured around the following objectives:
- Learning from Healthcare Organizations: Understand the health challenges with care fragmentation, gaps that contribute to poor decisions and thereby leading to unfavorable health outcomes, including but not limited to transitions of care, patient engagement, patient monitoring, health disparities, and access to rural healthcare.
- Showcasing Ongoing AI/ML Research: Present ongoing and pertinent research endeavors in the various topics of Artificial Intelligence and Machine Learning with respect to how to make AI explainable, how we improve methods to measure patient behavior, how to build AI on top of fragmented infrastructure.
- Identifying Synergies: Explore potential synergies between AI expertise and addressing the challenges impeding optimal health outcomes.
- Developing Use-Driven Research Problem Statements: Collaboratively formulate research problem statements grounded in practical applications and real-world healthcare needs.
Uniting stakeholders from various disciplines, we can foster a comprehensive understanding of the intersection between AI and healthcare, thereby paving the way for innovative solutions to pressing healthcare challenges.