Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...
BACKGROUND: Antidepressants play a crucial role in treating mental health disorders such as depression and anxiety. Understanding of patients' perspective on antidepressants is essential for improving treatment outcomes; however, year-to-year change ...
Cognitive behavioral therapy (CBT) and pharmacotherapy are primary treatments for major depressive disorder (MDD). However, their differential effects on the neural networks associated with rumination, or repetitive negative thinking, remain poorly u...
BACKGROUND: Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is univers...
Journal of chemical information and modeling
Jul 17, 2025
With the advancement of artificial intelligence-embedded methodologies, their application to predict fundamental molecular properties has become increasingly prevalent. In this study, a graph convolutional neural network fingerprint-enabled artificia...
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Jul 11, 2025
Despite advances in the treatment of major depressive disorder (MDD) yet a substantial proportion of patients fail to achieve remission and instead develop treatment-resistant depression (TRD). Identifying robust clinical predictors of response is es...
The Forced Swim Test (FST) is a widely used preclinical model for assessing antidepressant efficacy, studying stress response, and evaluating depressive-like behaviours in rodents. Over the last 10 years, more than 5500 scientific articles reporting ...
Research in social & administrative pharmacy : RSAP
Jun 24, 2025
BACKGROUND: A substantial cohort of individuals rely on online resources, such as discussion forums, for support on tapering antidepressants. This study aimed to assess the performance of generative artificial intelligence (AI) in responding to clini...
BACKGROUND: Depression is highly recurrent, and predicting relapses in a timely manner is critical. We applied machine learning to predict the worsening of depressive symptoms.
Major depressive disorder (MDD) presents a substantial health burden with low treatment response rates. Predicting antidepressant efficacy is challenging due to MDD's complex and varied neuropathology. Identifying biomarkers for antidepressant treatm...
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