New Method to Enrich Multi-Modal Longitudinal Data Accepted to AAAI 2020

Thu Jan 16, 2020

Lyujian Lu has recently had his paper, “Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments”, accepted into the proceedings of the 34th annual AAAI conference, AAAI 2020.

We’d also like to highlight Lauren Zoe Baker who is an undergraduate student who worked on this research. This is her second publication.

This research aims to combine multiple modalities across longitudinal data and provide an enriched representation that can work with classical supervised learning models to increase predictive performance. It does so by detecting global and local patterns within the longitudinal data and condensing them into an enriched representation that can be used for any task.

This work will be presented in February 2020 at the Hilton New York Midtown, New York City, NY, USA as part of AAAI 2020.