Latest AI and machine learning research in psychiatry for healthcare professionals.
Background and Objectives: Subjective cognitive decline (SCD), self-reported worsening confusion or memory over the past year, is a common early marker of cognitive concern with relevance for Alzheimer's disease prevention and population health. Population-based machine learning benchmarks that respect temporal drift in public health surveillance remain limited. We developed a reusable multi-langu...
Video Temporal Grounding (VTG) faces significant challenges when natural language queries must distinguish between multiple events involving visually similar entities, particularly when relying on fine-grained visual attributes that are difficult to describe accurately in words alone. To address this, we introduce Image-Disambiguated Video Temporal Grounding (ID-VTG), a task that leverages multimo...
Electroretinography (ERG) measures the functional response of distinct retinal cells to light, but was largely displaced by structural imaging in the ...
Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a "supervision gap" where novice therapists manage high...
Autism spectrum disorder (ASD) is a developmental disability characterized by challenges in social interaction and communication. As the causes of ASD...
Real-world decision-making rarely occurs with perfect information. Instead, individuals must constantly weigh potential rewards against the probabilit...
Background: Generative AI is evolving at a rapid pace, and many individuals are utilizing chatbots for mental health support. The safety of chatbots a...
Importance. Systematic reviews and meta-analyses inform suicide-prevention policy and practice, but broad database searches are difficult to screen ma...
Stigmatizing language in clinical documentation, which conveys negative stereotypes, attitudes, or judgments toward patients, is a recognized source o...
Objective: Foundation models represent the next advancement in AI for EEG analysis; however current explainable AI techniques provide attribution scor...
Dance imitation integrates motor planning, sensorimotor integration, and social cognition, offering a sensitive framework to characterize motor behavi...
The aim of this paper is to (1) identify textual and visual themes and sub-themes associated with the #wellbeing hashtag on Instagram, (2) assess thei...
Body-focused repetitive behaviors, such as hair pulling and skin picking, are compulsive motor actions commonly associated with obsessive-compulsive a...
Background: Large language models have been proposed to improve patient comprehension of radiology reports. However, whether they improve objective un...
This paper presents ECHO (Enhanced Care \& Health Observer), a locally-deployable conversational health assistant for long-term chronic care managemen...
Background. General purpose generative AI (GenAI) chatbots are increasingly used by students for mental health support. Research on prevalence estimat...
Synthetic generation of Cognitive Behavioral Therapy (CBT) sessions is challenged by two competing demands: adhering to strict therapeutic structure w...
Neurological and mental-health conditions such as Parkinson's disease (PD) and major depressive disorder (MDD) impose a substantial and growing global...
Large language models provide a promising framework for wearable-based health prediction by converting structured physiological and behavioral measure...
Cross-site identification of major depressive disorder (MDD) from resting-state functional magnetic resonance imaging (rs-fMRI) is hindered by inter-s...