Master's Thesis
Neuro-Symbolic Linguistic Analysis to Support the Diagnosis of Mental Illnesses
— 2025
Key information
Authors:
Supervisors:
Published in
October 24, 2025
Abstract
Bipolar Disorder and Psychosis are two mental health conditions that affect millions of people globally and pose serious public health challenges. Slow and inefficient healthcare systems are often unable to reach priority patients in time, further aggravating their condition. Although computational methods have demonstrated potential for supporting diagnosis, their clinical utility is frequently held back by their low explainability. Building upon current hypotheses on the relation between mental disorders and semantic memory, we present some preliminary work and results suggesting the potential of graph-based methods for the representation and interpretation of linguistic indicators to create a diagnosis-aiding tool for Psychosis and Bipolar Disorder. Therefore, we introduce a Heterogeneous Multilayer Network to model semantic, phonetic, and temporal aspects of speech, enabling nuanced and interpretable analysis. Additionally, we take a look at possible refinements to the European Portuguese Psychosis and Bipolar Disorder corpus to mitigate demographic imbalances, primarily focusing on a possible expansion of the Control group. Ultimately, we anticipate that this work could lead to a more scalable, language-agnostic, interpretable, and clinically useful framework for diagnosing these mental health conditions.
Publication details
Authors in the community:
Diogo Dinis
ist199066
Supervisors of this institution:
Alberto Abad Gareta
ist90700
Fields of Science and Technology (FOS)
electrical-engineering-electronic-engineering-information-engineering - Electrical engineering, electronic engineering, information engineering
Publication language (ISO code)
eng - English
Rights type:
Embargoed access
Date available:
September 10, 2026
Institution name
Instituto Superior Técnico