Introduction
The 2023 Machine Learning for Health (ML4H) Symposium is excited to introduce a new component to the program - the Call for Demonstrations. Increasing numbers of Machine Learning-based Software as Medical Devices are approved by organizations such as US FDA, China NMPA, or EU CE among others. As the ML4H field continues to mature and differentiate, there is a growing need for an interface where assumptions prevalent in ML4H research can be validated against the challenges, solutions, and maturity of real-world ML4H tools.
The ML4H Demo track aims at submissions that demonstrate real-world applications of ML4H technologies, bridging the gap from proof-of-concept to practical utility. Submissions will be evaluated according to the following process and criteria.
Submission Format and Review Process
A submission to the CfD consists of two components
- Filling out the submission form which is available here https://forms.gle/p289mcAa3wC7n2DFA including basic information such as
- Application domain
- Notable ML challenges and solutions faced, if any, during development and deployment of the tool
- Location of use and manufacture
- 1 page specsheet describing the ML4H tool technology and application. References and appendices, if needed, can be on extra pages, but we encourage you to keep the specsheet short and concise. The document will be submitted as part of the form above. Only .pdf files are accepted. Max file size 10MB. Please use the following LaTeX template to prepare your specsheet, available here
Drive: https://drive.google.com/file/d/1Kf-qwqwioNf_7UJx4FOGYzVFWoXXDWtY/view?usp=sharing
and
Overleaf: https://www.overleaf.com/read/mxmvxjznzkxm
All submissions will undergo a review process by the ML4H Demo Review Committee to uphold the selection criteria and assess the maturity and fit of the submitted demos.
Accepted submissions will have the opportunity to present their work in a poster-like live demo format on the day of the event and roundtables/plenary discussion.
Selection Criteria
All submitted demos will be evaluated based on the following selection criteria:
1. Relevance to the ML4H field
2. Maturity of the tool or project (e.g., used but approval not necessary, in approval process, approved by a notified body)
3. Quality and clarity of the submission
4. Highlighting the role of machine learning methods as a source of solutions or challenges during the development or deployment of the tool.
Important Dates
All dates in AoE
1. Call for Demos Opens: Monday, July 3, 2023
2. Submission Deadline: Friday, October 13, 2023
3. Acceptance Notification: Wednesday, November 1, 2023
4. Day of Presentation: Sunday, December 10, 2023
Contact and Questions
If you have any questions regarding your submission you can reach demo chairs at
- luis.oala@dotphoton.com (Luis, he/him)
- xushan@caict.ac.cn (Shan, she/her)
For general questions related to the Symposium please contact info@ml4h.cc.
We eagerly await your submissions. This is an opportunity to showcase the practical side of ML4H and demonstrate the impact smart machine learning learning solutions can have on improving health outcomes. We look forward to your participation in making the ML4H 2023 Symposium program a success!