Data Science, Informatics and Artificial Intelligence in Learning Healthcare System

In this presentation, Dr. Hongfang Liu delves into the convergence of data science, informatics, and AI in healthcare, focusing on evidence-based methodologies and people-centric AI applications. Through compelling projects in precision asthma care for pediatric patients and event surveillance in surgery, Dr. Liu envisions the transformative role of AI in augmenting healthcare practices, emphasizing the need for collaborative efforts to bridge the gap between AI research and practical applications.

1. Introduction to Data Science, Informatics, and AI
a. Speaker introduces her roles at McWilliams School of Biomedical Informatics and UTHealth Houston.
b. Emphasis on translating research and discoveries in AI into real-world applications in biomedicine and healthcare informatics.
c. Quote: "I'm one of the new faces at McWilliams School of Biomedical Informatics, focused on the translation of our wonderful biomedical and health informatics research and discovery into real-world applications benefiting healthcare."
Time Stamp: 00:10-1:04

2. Digital Transformation in Healthcare
a. Discussion on digital transformation in healthcare, leveraging big data for achieving the mission outlined by President Barack Obama.
b. Emphasis on lowering healthcare costs, reducing medical errors, and improving care through computerized healthcare data.
c. Quote: "We are now in an exciting era of digital transformation in healthcare. By effectively deploying AI, we can help UTHealth Houston to better achieve its mission to advance patient care and improve organizational efficiency."
Time Stamp: 1:04-2:40
3. Role of Data Science and Informatics
a. Highlighting data science and informatics as engines for concepts in precision medicine and learning healthcare systems.
b. Importance of leveraging data to accelerate data-driven healthcare delivery.
c. Quote: "Data science and informatics are seminal engines that enable us to leverage the power of data to accelerate data-driven healthcare delivery, thus making precision medicine possible."
Time Stamp: 2:41-4:33

4. Vision for the Future Learning Healthcare System
a. Envisioning the future Learning Healthcare System at UTHealth Houston by integrating advanced technology and continuous learning.
Time Stamp: 4:34-5:59

5. Translation Science and Application Examples
a. Introduction to translation science as a focus, emphasizing the translation of discoveries into applications to address real-world problems.
b. Illustration of two projects: precision asthma care for pediatric asthma management and EHR-based event surveillance for surgery risk prediction.
Time Stamp: 6:00-14:32

6. Challenges and Considerations
a. Discussion of challenges, including patient volume, data sparseness, computational costs, and the need for alternative learning strategies.
b. Recognition of real-world issues such as structural barriers, discrimination, and imperfect healthcare systems.
Time Stamp: 14:33-17:46

7. Goal of Bringing AI into Healthcare Practice
a. Emphasis on bringing AI technology into healthcare practice through evidence-based approaches, people-centric technology, and demonstrating value.
b. Quote: "The goal for our TEAM-AI center at McWilliams School of Biomedical Informatics is to successfully integrate AI technology into healthcare practice, showing the value that we bring to clinical practice."
Time Stamp: 17:47-18:24