Events
AMIA Webinar | The Good, the Bad, and the Ugly of Real-World AI Use
Date
September 18, 2024 01:00pm - 02:00pm
US/Eastern
Join experts from RTI International for an insightful webinar hosted by the American Medical Informatics Association (AMIA) exploring the transformative impact of AI in health care, informatics, and the research community. The webinar will begin with a brief overview of AI’s role in the sector, highlighting its integration with Clinical Decision Support (CDS) systems, applying AI in large-scale Electronic Health Record (EHR) Data Repositories, and how Large Language Models (LLMs) are more than just generative AI. Then, the presenters will delve into two practical application examples, showcasing AI’s real-world benefits. The session will conclude with an examination of AI governance, ensuring ethical and effective implementation.
Attendees will learn about:
- responsible use of AI in health care through real-world applications;
- applications of AI in large-scale EHR Data Repositories; and
- the capabilities of LLMs for novel approaches to text analysis.
By the end of the webinar, participants will have a comprehensive understanding of AI’s current and potential future roles in health care, practical insights from real-world applications, and knowledge of the governance frameworks essential for ethical AI implementation.
Meet the Presenters
Laura Marcial, PhD
Laura Marcial, PhD, is the Senior Director of the Center of Informatics at RTI, providing leadership across bioinformatics, environmental toxicology, and biomedical informatics teams. Dr. Marcial has been leading work on groundbreaking health information technology-related projects, including the automated movement of clinical data for research purposes at scale, the development of CDS tools, the study of patient-provider engagement, and the use of social media and mobile technologies.
Jamie Pina, PhD
Jamie Pina, PhD, is the Scientific Director of Public Health Technology at RTI and works to solve mission-driven challenges with cutting-edge public health and biomedical information systems. Dr. Pina’s recent work energizes and enhances national data architectures for public health and biomedical research, exploring the use of health equity data models and integrating generative AI into public health practice to improve efficiency.
Daniel Brannock
Daniel Brannock is a research data scientist who applies data science across health care data and applications, particularly real-world data and EHRs. As part of the National Institutes of Health-funded Researching COVID to Enhance Recovery initiative, Mr. Brannock is using EHRs from tens of millions of patients available in the National COVID Cohort Collaborative to characterize and search for treatments for Long COVID.
Emily Hadley
Emily Hadley is a research data scientist with technical skills in machine learning, forecasting, generative AI, natural language processing, predictive analytics, and data visualizations, along with extensive experience programming in Python and R. Ms. Hadley collaborates with other technical contributors and subject matter experts on applied data science projects across various focus areas, including health, education, social policy, and criminal justice.
