Review and content analysis of textual expressions as a marker for depressive and anxiety disorders (DAD) detection using machine learning

CM Sharma, D Damani, VM Chariar - Discover Artificial Intelligence, 2023 - Springer
Depressive disorders (including major depressive disorder and dysthymia) and anxiety
(generalized anxiety disorder or GAD) disorders are the two most prevalent mental illnesses …

Empowering short answer grading: Integrating transformer-based embeddings and BI-LSTM network

WH Gomaa, AE Nagib, MM Saeed, A Algarni… - Big Data and Cognitive …, 2023 - mdpi.com
Automated scoring systems have been revolutionized by natural language processing,
enabling the evaluation of students' diverse answers across various academic disciplines …

CDME-GAT: Context-Aware Depression Detection Using Multiembedding and Graph Attention Networks in Social Media Text

M Jain, S Jain, A Jain, B Garg - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Depression, a prevalent mental health concern, requires timely identification and
intervention. Automating the early stage identification of depression cues within social media …

A Friend in Need Is a Friend Indeed: Investigating the Quality of Training Data from Peers for Auto-generating Empathetic Textual Responses to Non-Sensitive Posts in …

R Sharma, J Mirzakhalov, P Bharti, R Goyal… - ACM Journal on …, 2023 - dl.acm.org
Towards providing personalized care, digital mental-wellness apps today ask questions to
learn about subjects. However, not all subjects using these apps will have mood problems; …

Enhancing Depression Detection through Advanced Text Analysis: Integrating BERT, Autoencoder, and LSTM Models

N Firoz, OG Beresteneva, AS Vladimirovich, MS Tahsin - 2023 - researchsquare.com
Depression is a austere medical ailment that upsets numerous people worldwide, causing a
persistent decrease in mood and significantly impacting their emotions. The article focuses …

AI-Enhanced Mental Health Diagnosis: Leveraging Transformers for Early Detection of Depression Tendency in Textual Data

S Verma, RC Joshi, MK Dutta, S Jezek… - … Congress on Ultra …, 2023 - ieeexplore.ieee.org
Early detection and treatment of depression depend critically on mental health assessment.
Artificial intelligence-based methods have shown potential in assessing linguistic and …

A Literature Review on the Detection of Mental Illness

S Shaik, VC Bharathi - 2024 5th International Conference on …, 2024 - ieeexplore.ieee.org
One of the most frequent psychological disorders is depression. The major challenge is a
quick and accurate diagnosis of the condition. Self-reporting surveys are the tools that …

[PDF][PDF] CULTIVATING RESILIENCE: A TRANSFORMATIVE APPROACH TO ENHANCING CLOUD DATA SECURITY WITH TRANSFORMER-BASED TECHNIQUES

G Prabhakar, BB Rao - Proceedings on Engineering, 2024 - researchgate.net
Data centres have grown drastically in size and in number as the digital economy has
proliferated. For the advancement of society and the economy, data centres are becoming …

An Extensive Diagnosis System of Early Depression Symptoms using Machine Learning Algorithm

KM Anandkumar, S Ajith… - 2023 3rd …, 2023 - ieeexplore.ieee.org
Suicidal deaths caused by depression have been an emerging crisis worldwide and is
predicted by the World Health Organization (WHO) to accelerate to a much bigger scale …

Dual Layer Cogni-Insight Deep-Mood Encoder: A Two-Tiered Approach for Depression Detection

N Firoz, O Berestneva… - … Russian Smart Industry …, 2024 - ieeexplore.ieee.org
Depression (MDD) affects approximately 5% of adults globally, contributing to productivity
loss and public health concerns. With 280 million people impacted, the risk of suicide and …