Deadline: May 13, 2020
Notifications: June 17, 2020
Workshop: July 18, 2020
This workshop will feature cross-disciplinary speakers, aiming to represent a diverse set of the problems global health seeks to address. We welcome short (two-page) abstracts from the machine learning, global health and related communities which would be of interest to the attendees of the machine learning for global health workshop.
Topics may include but are not limited to:
- Outbreak and pandemic detection and forecasting
- Challenges of resource-constrained health contexts
- Deployment of early-detection systems
- Machine learning applied to understanding infectious diseases
- Understanding and preventing child mortality and other problems in public health
- Challenges in translation between healthcare systems
Selected abstracts will be invited for presentation as either a poster or a talk spotlight. There will be no archival proceedings and we allow for recently-published work.
Abstracts should be no more than 2 A4 pages long (excluding references), in PDF or Word format. They should not be blind.
As we expect cross-disciplinary work, please highlight the relevance for both the machine learning and global health communities.
Original research, recently-published work, and position pieces are acceptable.
Submit your abstract via CMT here.
Submission deadline: 13th May, 2020 (Anywhere on Earth, AoE)
Author notification: 17th June, 2020
Workshop date: 18th July, 2020