Latest AI and machine learning research in anxiety & stress for healthcare professionals.
Physical simulations for intricate geometries with path-dependent constitutive models face difficulties due to the enormous computational cost they require. Recently, the emergence of generative AI models, which succeed in image and video synthesis tasks, has provided a promise to further improve simulations. Although U-Net-based denoising diffusion probabilistic models (DDPMs) have been adopted f...
Mental health assessment commonly relies on isolated screening instruments or data-driven models that often lack interpretability and multi-dimensional integration. Existing approaches frequently focus on individual indicators such as depression or anxiety while providing limited support for comprehensive and explainable decision-making. To address this limitation, this study proposes PsyBridge, a...
Understanding how neuronal morphology changes during aging and acute stress is essential for elucidating mechanisms of neurodegeneration. The highly b...
Question Are adverse childhood experiences (ACEs) associated with altered growth trajectories in childhood? Findings In this cohort study of 412,549 c...
Diffusion models are increasingly used to predict transcriptional responses to perturbations, but whether they improve on simpler generative and repre...
Industrial anomaly detection suffers from limited data, making cross-domain generalization particularly challenging. Generalist Anomaly Detection (GAD...
Anxiety and depression are globally prevalent conditions associated with maladaptive decision making. However, whether affective symptoms primarily am...
Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are di...
Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successi...
Cells maintain homeostasis by dynamically reorganizing their organelles to tune metabolism in response to stress. Fluorescence microscopy maps organel...
Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised ...
Background: Generative AI tools can support data-intensive research by writing code, drafting prose, searching analytical possibilities, and stress-te...
Insulin therapy for type 1 diabetes requires continual dose adjustment to meals, activity, stress, illness, and changing insulin sensitivity, creating...
Impaired learning that both novel and previously dangerous stimuli are safe (safety and extinction learning, respectively) are long standing, robust, ...
Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current c...
Introduction: Large-scale free-text data with socio-demographic information can capture nuanced accounts of lived experience that are difficult to det...
Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. The gut microbio...
Background: Aberrations in neuro-immune, metabolic, and oxidative stress (NIMETOX) pathways are implicated in major depressive disorder (MDD). First-e...
The ability to adjust to changing environments (cognitive flexibility) and optimal decision-making are pivotal brain functions that govern successful ...
Potato crop is highly vulnerable to abiotic stresses like salinity and low nutrient availability. Rapid identification of stress-resilient genotypes i...