Background: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from social media provides new insights into predicting ...

Department of Chemistry, Zhongshan Hospital, Fudan University, Shanghai 200000, China Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200092 ...

The field of psychiatry has long been grappling with the complexities of mental disorders, which are often characterized by heterogeneous presentations and multifactorial etiologies. Traditional ...

The battle to distinguish human writing from AI-generated text is intensifying. And, as models like OpenAI’s GPT-4, Anthropic’s Claude and Google’s Gemini blur the line between machine and human ...

Statistical learning (SL) is a fundamental cognitive ability enabling individuals to detect and exploit regularities in environmental input. It plays a crucial role in language acquisition, perceptual ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

Abstract: Emotion classification in social media texts has several challenges, such as the characteristics of social media texts that tend to use informal language, unbalanced data distribution, ...

ABSTRACT: This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis.

The manuscript provides important new insights into the mechanisms of statistical learning in early human development, showing that statistical learning in neonates occurs robustly and is not limited ...