Papers by Bart Desmet
Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires (2022.acl-long)
Copied to clipboard
| Challenge: | Existing approaches to identify mental health conditions using social media are limited by the presence of symptoms described in a questionnaire used by clinicians. |
| Approach: | They propose to ground a model in PHQ9's symptoms to improve generalization . they also show that this approach can still perform competitively on in-domain data. |
| Outcome: | The proposed approach can perform competitively on in-domain data while improving generalizability and generalisability. |
SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions (C18-1)
Copied to clipboard
| Challenge: | Existing methods to label mental health conditions are based on high-precision diagnosis patterns and carefully selected control users. |
| Approach: | They propose to use high-precision diagnosis patterns to identify self-reported diagnoses of nine different mental health conditions and obtain high-quality labeled data without manual labelling. |
| Outcome: | The proposed dataset is two orders of magnitude larger than the largest published similar resource. |
A Whole-Person Function Dictionary for the Mobility, Self-Care and Domestic Life Domains: a Seedset Expansion Approach (2022.lrec-1)
Copied to clipboard
Ayah Zirikly, Bart Desmet, Julia Porcino, Jonathan Camacho Maldonado, Pei-Shu Ho, Rafael Jimenez Silva, Maryanne Sacco
| Challenge: | Functional limitations affect a large proportion of the world's population, according to the World Health Organization. |
| Approach: | They propose to use a set of manually annotated clinical notes to build a terminology for whole-person function in the domains of mobility, self-care and domestic life. |
| Outcome: | The proposed terminologies were built and evaluated using a small set of manually annotated clinical notes. |
QA4IE: A Quality Assurance Tool for Information Extraction (2022.lrec-1)
Copied to clipboard
| Challenge: | Existing tools for data annotation do not provide comprehensive support for quality assurance. |
| Approach: | They propose a QA tool for information extraction that detects potential problems in text annotations in a timely manner and accurately assesses the quality of annotations. |
| Outcome: | The proposed tool can detect potential problems in text annotations in a timely manner, accurately assess the quality of annotations, and visually display and summarize annotation discrepancies among annotation team members. |