Latest AI and machine learning research in psychiatry for healthcare professionals.
The current state of mental health treatment for individuals diagnosed with major depressive disorder leaves billions of individuals with first-line therapies that are ineffective or burdened with undesirable side effects. One major obstacle is that distinct pathologies may currently be diagnosed as the same disease and prescribed the same treatments. The key to developing antidepressants with ubi...
Higher-level action interpretation, such as inferring underlying intentions and predicting future actions, requires the integration of conceptual action information (e.g. "opening") with semantic knowledge about persons and objects (e.g. "my friend Anna", "pizza box"). However, how the neural systems for action and object recognition and memory interact with each other to form the basis for inferr...
A central objective in human neuroimaging is to understand the neurobiology underlying cognition and mental health. Machine learning models trained on...
Cognitive control supports adaptive responses in an ever-changing world. While alterations in cognitive control have been consistently observed in a r...
Pavlovian avoidance enables rapid defensive responding but can undermine goal-directed behaviour when it overrides instrumental control, a tendency am...
Generalized anxiety disorder (GAD) is characterized by chronic worry and emotional dysregulation, yet its underlying white matter (WM) architecture re...
Recent studies have demonstrated strong associations between the changes in dynamic functional connectivity (FC) and both behavioral and cognitive fun...
Autism Spectrum Disorder (ASD) is a developmental disorder characterized by heterogeneity in social and emotional responses, language, and behavior. A...
The CACNA1C gene encodes the CaV1.2 L-type voltage-gated calcium channel, which plays a crucial role in neuronal signaling. CACNA1C is a risk gene for...
Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depr...
Schizophrenia (SCZ) is a neurodevelopmental disorder where both genetic and environmental risks converge during pregnancy. Recent studies have highlig...
To characterize cell type specific transcriptional changes during human retinal aging and develop machine learning model for cellular age discriminati...
Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...
Large language models (LLMs), such as GPT-4, are increasingly integrated into healthcare to support clinicians in making informed decisions. Given Cha...
Schizophrenia spectrum disorders (SSD) are associated with accelerated brain aging, reflected in an increased brain age gap. This gap serves as a biom...
Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...
Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chronic (cLBP). Optimal diagnostic tools for cLBP remai...
Suicide is a critical medical and public health challenge, particularly among individuals with mental illnesses in safety-net hospitals. To uncover in...
To determine whether historical behavior data can predict the occurrence of high-risk behavioral or seizure events in individuals with profound Autism...
Patient satisfaction is a central measure of high-performing healthcare systems, yet real-world evaluations at scale remain challenging. In this study...