In partnership with the World Federation of Pediatric Intensive & Critical Care Societies (WFPICCS), the Pediatric Sepsis Data CoLaboratory (Sepsis CoLab) is facilitating a WFPICCS 2022 Pre-Congress Workshop on Data-driven sepsis research: an international data challenge to develop risk prediction models for pediatric sepsis mortality.
When: 13 July 2022 | 13:15 – 17:30 SAST (04:15 – 08:30 PDT)
Where: Virtual
At this workshop, the Sepsis CoLab, in partnership with
Emory University and
PhysioNet, will be launching an
international data challenge to develop risk prediction models for pediatric sepsis mortality.
Join us to learn more about the Sepsis CoLab, sepsis research, QI initiatives, and to participate in the launch of our data challenge! By participating in this challenge, you will be able to collaborate with participants from around the world to build skills in model development. This year-long data challenge is open to all! You do not need to be an expert to participate.
If you’d like to attend, please register for workshop W19.
- Introduction to the Pediatric Sepsis Data Colaboratory
- Mark Ansermino – Director, Centre for International Child Health, BC Children's Hospital, and Professor, Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia
- Overview of sepsis research + QI, from developing projects to managing data
- Yashodani Pillay – Postdoctoral Fellow, Centre for International Child Health, BC Children's Hospital, and University of British Columbia
- Implementing tools for real time data collection and data-driven QI in the pediatric outpatient department at Jinja Regional Referral Hospital in Uganda
- Abner Tagoola – Head of Department Pediatrics, Jinja Regional Referral Hospital
- Developing a risk-stratification model to support QI in post-discharge care for children treated with sepsis at 4 public health facilities across Uganda
- Clare Komugisha - Nurse Coordinator, Walimu
- Matthew Wiens – Investigator, Centre for International Child Health, BC Children's Hospital, and Assistant Professor, Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia
- Machine Learning for Health in LMICs: Experiences from applications in the field
- Gari Clifford – Chair, Department of Biomedical Informatics, Emory University, and Professor, Emory University and Georgia Institute of Technology
- Bias and Fairness in Machine Learning: What are the consequences for generalizable health AI
- Matthew Reyna – Professor, Department of Biomedical Informatics and Department of Pharmacology and Chemical Biology, Emory University, and Vice Chair for Education and Training, Department of Biomedical Informatics, Emory University.
- Introduction to the Data Challenge: Rules and standard practices
- Rishikesan Kamaleswaran – Assistant Professor, Department of Biomedical Informatics, Emory University
