Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

Mental health research through data-driven methods has been hindered by a lack of
standard typology and scarcity of adequate data. In this study, we leverage the clinical …

The influence of social media is one of the most dominating characteristics of the current era,
and this has led cyberbullying to grow into a more serious social issue. As a result …

Depression is a mental state characterized by recurrent feelings of melancholy,
hopelessness, and disinterest in activities, having a significant negative influence on …

Cyberbullying is a growing concern in the digital age, causing significant harm to its victims.
The ability to automatically detect cyberbullying in social media is crucial for protecting …

In public health surveillance, the identification of Personal Health Mentions (PHM) is an
essential initial step. It involves examining a social media post that mentions an illness and …

As social media has become a predominant mode of communication globally, the rise of
abusive content threatens to undermine civil discourse. Recognizing the critical nature of …

Cyberbullying is the spreading of hate among different religions and people through the
Internet. With the worldwide growth in Twitter users, it is now more prone to bullying. There …

The main aim of this paper is to propose malicious detection and prevention by providing the
data confidentiality framework using deep learning models of Long Short-Term Memory …

Accurate classification of organs from medical images plays a vital role in modern medicine.
The recent improvements in science and technology, computational resources, and data …