Deep learning for the prediction of treatment response in depression
L Squarcina, FM Villa, M Nobile, E Grisan… - Journal of affective …, 2021 - Elsevier
Background Mood disorders are characterized by heterogeneity in severity, symptoms and
treatment response. The possibility of selecting the correct therapy on the basis of patient …
treatment response. The possibility of selecting the correct therapy on the basis of patient …
Depression detection from social networks data based on machine learning and deep learning techniques: An interrogative survey
KM Hasib, MR Islam, S Sakib, MA Akbar… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Users can interact with one another through social networks (SNs) by exchanging
information, delivering comments, finding new information, and engaging in discussions that …
information, delivering comments, finding new information, and engaging in discussions that …
Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media
The ability to explain why the model produced results in such a way is an important problem,
especially in the medical domain. Model explainability is important for building trust by …
especially in the medical domain. Model explainability is important for building trust by …
Explainable zero-shot modelling of clinical depression symptoms from text
We focus on exploring various approaches of Zero-Shot Learning (ZSL) and their
explainability for a challenging yet important supervised learning task, notorious for training …
explainability for a challenging yet important supervised learning task, notorious for training …
[HTML][HTML] EEG based depression detection by machine learning: Does inner or overt speech condition provide better biomarkers when using emotion words as …
Background Objective diagnostic approaches need to be tested to enhance the efficacy of
depression detection. Non-invasive EEG-based identification represents a promising area …
depression detection. Non-invasive EEG-based identification represents a promising area …
Depression symptoms modelling from social media text: A semi-supervised learning approach
N Farruque, R Goebel, S Sivapalan… - arXiv preprint arXiv …, 2022 - arxiv.org
A fundamental component of user-level social media language based clinical depression
modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any …
modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any …
Analysis of Covid-19 misinformation in social media using transfer learning
Most major events are often accompanied by misinformation on online Social Networking
platforms. Due to its nature, the COVID-19 pandemic was bound to lead to an explosion of …
platforms. Due to its nature, the COVID-19 pandemic was bound to lead to an explosion of …
Depression symptoms modelling from social media text: an LLM driven semi-supervised learning approach
N Farruque, R Goebel, S Sivapalan… - Language Resources and …, 2024 - Springer
A fundamental component of user-level social media language based clinical depression
modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any …
modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any …
Multimodal depression detection using machine learning
R Jahan, MM Tripathi - Artificial Intelligence, Machine Learning, and Mental …, 2022 - Elsevier
Depression is a mood disorder that includes feelings of sadness, loss, or anger. It interferes
with a person's daily activities. People express frustration in various ways. Some people …
with a person's daily activities. People express frustration in various ways. Some people …
Predicting depression and suicide ideation in the Canadian population using social media data
R Skaik - 2021 - ruor.uottawa.ca
The economic burden of mental illness costs Canada billions of dollars every year. Millions
of people suffer from mental illness, and only a fraction receives adequate treatment …
of people suffer from mental illness, and only a fraction receives adequate treatment …