ICCAI 2020: Meaningful AI in the Age of COVID-19
The upcoming ICCAI’2020 Conference, titled “Meaningful AI in the Age of COVID-19”, will be held on September 10-11, 2020.
Register here!
ICCAI is the annual meeting of the Society for Complex Acute Illness (SCAI), which, since its inception over 15 years ago, has successfully bridged the domains clinical practice of critical care medicine and quantitative approaches to understanding critical illness, with a strong translational focus. On the methodological side, it has emphasized eclecticism, covering, through its interdisciplinary membership, modeling approaches ranging from pure mechanistic differential equations models and agent-based models to purely data-driven machine learning techniques.
We strongly believe that a smart and flexible combination of techniques leveraging individual strength of each approach where appropriate is the only way to successfully address the complexity of real-world problems in acute illness and will showcase this at ICCAI-2020.
Given the historical circumstances brought about by the COVID-19 pandemic, ICCAI’2020 will be conducted entirely online, using Zoom teleconferencing technology. Download the full program here(PDF) or see below.
Full Program
All Times are Eastern Time
| Day 1 Introduction | Thursday, September 10, 2020 |
| 8:50 – 9:00 | Introduction by SCAI President Gilles Clermont |
| 9:00 – 9:30 | AI in Acute Care: Is it fall or spring? – M. Matheny (Vanderbilt Univ. Medical Ctr) |
| 9:30- 12:30 Thematic session I: | Knowledge-driven AI for injury and critical care: Blending Data and Mechanism Session Chair: Gary An P1. Functional hemodynamics and closed-loop resuscitation—M. Pinsky (Univ. of Pittsburgh) P2. Model-driven AI for wound healing—Y. Vodovotz (Univ. of Pittsburgh) 10:30-10:45 Morning Break P3. Causal models as core therapeutic engines—O. Gajic (Mayo Clinic) P4. Reinforcement learning: offline and online—M. Komorowski (Imperial College) Discussion round table: Can data-driven AI work in complex illnesses? |
| 12:30-13:30 | Lunch Break |
| 13:30-16:30 Thematic Session II: | Does more data imply more clinical value? Session Chair: Beth Lusczek P5. Pervasive sensing in critical care—A. Bihorac and P. Rashidi (Univ. of Florida) P6. Wearable and embedded sensors, how can they help?—H. Dohse (Tour de Heart) P7. The sepsis transcriptome for treatment selection and prediction—H Wong (Cincinnati Children’s Hosp. Med.Ctr) 15:00-15:15 Afternoon break P8. Classification and predictive enrichment—C. Calfee (UCSF) Discussion round table: More data, more power? |
| Day 2 | |
| 9:00-9:30 | Reflection to honor 9/11 Keynote address: The future of AI in Health Care—Leo Celi (MIT, Harvard Medical School) |
| 9:30-12:30 Thematic session III: | Collaborative Research in Data Science: Strength in Diversity Session Chair: Gilles Clermont P9. The ESICM/SCCM Data Science Joint Task Force: Vision and Mission—G. Martin (Emory Univ.) P10. Opportunities for collaborative data science in neurocritical care—R. Stevens (Johns Hopkins Univ.) P11. Data Standardization and Harmonization: proximal challenges—A. Ercole (Cambridge Univ.) 10:30-10:45 Morning Break P12. Developing Good Machine Learning Practice—D. Maslove (Queen’s University) P13. Learning and validating across environments: tools and examples—C. Hinske (Univ. of Munich) Discussion round table: A common vision for critical care |
| 12:30-13:30 | Lunch break |
| 13:30-15:30 Thematic session IV: | AI and Data Science for COVID-19: Blending Mechanism and Data Science Session Chair: Yoram Vodovotz P.14 Clinical features of COVID-19 patients—S. Park (Columbia Univ.) P.15 Using AI to forecast adverse advents in COVID-19 patients—C. Barrett (UVa) P.16 Forecasting impact of COVID-19: Pros and cons of pandemic prediction models—Carson Chow (NIH) P.17 Mechanistic modeling of inflammation/immunity in COVID-19—Judy Day (Univ. of Tennessee) Discussion round table: Meaningful modeling for COVID-19 |
| 15:30-15:45 | Afternoon Break |
| 15:45-17:00 Thematic session V: | From Data to Action: Impactful AI Session Chair: Matt Churpek P18. Using a healthcare system- based AI unit to address system challenges —C. Umscheid (Univ. of Chicago) P19. From Prediction to Action – eCART to Pathways—M. Churpek (Univ. of Wisconsin) P20. Predictive Analytics Monitoring at the Bedside—R. Moorman (UVa) Discussion round table: Translating algorithms to patient care |
| 17:00 – 17:30 | Meeting wrap-up and Conclusions: Tim Buchman (Emory Univ.) |
| 17:30-18:00 | SCAI business meeting |
Register here!
If you need further information or have additional inquiries, please contact Dr. Zamora at zamorar@pitt.edu. We look forward to your attendance.
SCAI 2020 Scientific Program
Gilles Clermont, MD
Sven Zenker, MD
Ruben Zamora, PhD
Beth Lusczek, PhD
Yoram Vodovotz, PhD