Call for Demonstrations

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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.

Accepted submissions will be non-archival and have the opportunity to present their live demo on the day of the event.

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

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.

More details to come!