[HTML][HTML] Identifying predictive biomarkers for repetitive transcranial magnetic stimulation response in depression patients with explainability

M Squires, X Tao, S Elangovan, R Gururajan… - Computer Methods and …, 2023 - Elsevier
Abstract Repetitive Transcranial Magnetic Stimulation (rTMS) is an evidence-based
treatment for depression. However, the patterns of response to this treatment modality are …

Development and validation of a prediction score to assess the risk of depression in primary care

F Lapi, G Castellini, V Ricca, I Cricelli, E Marconi… - Journal of Affective …, 2024 - Elsevier
Background Major depression is the most frequent psychiatric disorder and primary care is a
crucial setting for its early recognition. This study aimed to develop and validate the DEP …

Leveraging Weak Supervision and BiGRU Neural Networks for Sentiment Analysis on Label-Free News Headlines

A Jamali, S Alipour, A Rah - 2024 IEEE 3rd International …, 2024 - ieeexplore.ieee.org
Auto-labeling of text is a useful and necessary technique for creating large and high-quality
training data sets for machine learning models. Label-free sentiment classification is a …

The optimized Neural Networking scheme in Time Series Analysis for Detecting Depression

M Pandeya, S Yadav, R Murugan - … International Conference on …, 2024 - ieeexplore.ieee.org
This study offers the Optimized Neural Networking scheme in time series analysis for
detecting depression. The proposed scheme uses Deep learning strategies, including …

State Space Model-based Classification of Major Depressive Disorder Across Multiple Imaging Sites

S Li, B Yang, T Ma, C Ye - Artificial Intelligence and Data Science for … - openreview.net
Major Depressive Disorder (MDD) is a prevalent psychiatric condition characterized by
persistent sadness and cognitive impairments, with high recurrence rates. This paper …