Exploiting textual and numerical data to improve predictive models for depression

For the effective treatment of depression more and more therapies are becoming available that exploit computer technology, for example in the form of therapist guided self-help modules on the Internet or more advanced support systems such as being developed in the FP7 ICT4Depression project coordinated by the Computer Science Department of the VU University Amsterdam. In the latter project, a first attempt is made to incorporate predictive models for people suffering from a depression, thereby allowing the system to predict what the course of a depression will be for a particular patient and how effective a certain therapy will be. In these attempts however, the wealth of data about depressed patients which is nowadays present has not been considered fully yet. This wealth includes data about the development of the mental state of patients over time, their involvement in the therapy such as their adherence and homework assignments they performed and their monitoring of mood and activities and keeping up with free text diaries.
Utilizing such data opens new ways to improve computational models for depression. In this project, we propose to: (1) interpret free text in a large dataset from the domain of depression using sentiment analysis techniques; hereby, the actual self-reported mood ratings that are also part of the data set can be used as validation; (2) validate an existing predictive computational model for depression using the (interpreted) dataset, and (3) try to generate enhancements to the computational model by applying learning techniques upon the dataset (more in specific, Genetic Programming).

Student Research Assistants:

Plamen Dimitrov
MSc Computer Science
E-mail: p.dimitrov@student.vu.nl

Reinier Kop
MSc Artificial Intelligence
E-mail: r2.kop@student.vu.nl


Mark Hoogendoorn
Department of Computer Science
VU University Amsterdam

Michel Klein
Department of Computer Science
VU University Amsterdam

Piek Vossen
Department of Language, Cognition and Communication (LCC)
VU University Amsterdam

Heleen Riper
Department of Clinical Psychology
VU University Amsterdam