End-to-end multimodal system for depression detection from online recordings.

Depression is one of the most occurring civilizational diseases. In this paper, we propose a new approach for detecting depression through the analysis of social media content using face analysis, emotion recognition neural networks, and speech processing. We utilized audio-visual analysis and acquired more than 605 features in the time domain.

Grid-supported Medical Digital Library.

Secure, flexible and efficient storing and accessing digital medical data is one of the key elements for delivering successful telemedical systems. To this end grid technologies designed and developed over the recent years and grid infrastructures deployed with their use seem to provide an excellent opportunity for the creation of a powerful environment capable of delivering tools and services for medical data storage, access and processing. In this paper we present the early results of our work towards establishing a Medical Digital Library supported by grid technologies and discuss future directions of its development.