Search Results for author:
Found 2 papers, 0 papers with code
Digital Phenotyping for Adolescent Mental Health: A Feasibility Study Employing Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data
Objective: Using a novel machine learning framework, this study evaluated the feasibility of integrating active and passive smartphone data to predict mental disorders in non-clinical adolescents.
Speaker-Independent Dysarthria Severity Classification using Self-Supervised Transformers and Multi-Task Learning
We develop a transformer framework, called Speaker-Agnostic Latent Regularisation (SALR), incorporating a multi-task learning objective and contrastive learning for speaker-independent multi-class dysarthria severity classification.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
