Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …

Social media is now being used to model mental well-being, and for understanding health
outcomes. Computer scientists are now using quantitative techniques to predict the …

Users of social media often share their feelings or emotional states through their posts. In
this study, we developed a deep learning model to identify a user's mental state based on …

Mental illnesses, such as depression, are highly prevalent and have been shown to impact
an individual's physical health. Recently, artificial intelligence (AI) methods have been …

Psychological health, ie, citizens' emotional and mental well-being, is one of the most
neglected public health issues. Depression is the most common mental health issue and the …

Psychiatry today must gain a better understanding of the common and distinct
pathophysiological mechanisms underlying psychiatric disorders in order to deliver more …

Large language models (LLM) have been successful in several natural language
understanding tasks and could be relevant for natural language processing (NLP)-based …

Abstract Machine and deep learning methods, today's core of artificial intelligence, have
been applied with increasing success and impact in many commercial and research …

Detection at an early stage is vital for the diagnosis of the majority of critical illnesses and is
the same for identifying people suffering from depression. Nowadays, a number of …