Psychiatry

Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations.

We propose a novel integrated framework that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imaging (DTI) tractography to extract biomarkers of brain connectivity predictive of behavior. Our framework couples a generative model of the connectomics data with a deep network that predicts behavioral scores. The generative compone...

Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level.

Depression is a severe psychological condition that affects millions of people worldwide. As depression has received more attention in recent years, it has become imperative to develop automatic methods for detecting depression. Although numerous machine learning methods have been proposed for estimating the levels of depression via audio, visual, and audiovisual emotion sensing, several challenge...

Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth.

Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data...

Towards an AI Coach to Infer Team Mental Model Alignment in Healthcare.

Shared mental models are critical to team success; however, in practice, team members may have misaligned models due to a variety of factors. In safet...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete....

Design of a Robotic Coach for Motor, Social and Cognitive Skills Training Toward Applications With ASD Children.

Socially assistive robots may help the treatment of autism spectrum disorder(ASD), through games using dyadic interactions to train social skills. Exi...

From everyday life predictions to suicide prevention: Clinical and ethical considerations in suicide predictive analytic tools.

Advances in artificial intelligence and machine learning have fueled growing interest in the application of predictive analytics to identify high-risk...

Reproducibility of automated habenula segmentation via deep learning in major depressive disorder and normal controls with 7 Tesla MRI.

The habenula is one of the most important brain regions for investigating the etiology of psychiatric diseases such as major depressive disorder (MDD)...

Polydopamine coated hypodermic needles as a microextraction device for the determination of tricyclic antidepressants in oral fluid by direct infusion MS/MS.

In-needle microextraction consists of the confinement of the sorbent, by coating or packing, inside a metallic needle. The size of the needles reduces...

Replication of machine learning methods to predict treatment outcome with antidepressant medications in patients with major depressive disorder from STAR*D and CAN-BIND-1.

OBJECTIVES: Antidepressants are first-line treatments for major depressive disorder (MDD), but 40-60% of patients will not respond, hence, predicting ...

A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.

Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal commu...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine lea...

Identifying Mobile Sensing Indicators of Stress-Resilience.

Resident physicians (residents) experiencing prolonged workplace stress are at risk of developing mental health symptoms. Creating novel, unobtrusive ...

Risperidone Reduces Matrix Metalloproteinase-9 and Increases Neurotrophin-3 in Schizophrenia Spectrum of Disorder.

Even though earlier studies have reported alteration in the markers of synaptic plasticity (Matrix metalloproteinase-9 [MMP-9] and Neurotrophin-3 [NT-...

Progress, challenges and global approaches to rare diseases.

Rare diseases occur globally at every stage of life. Patients, families and caregivers have many unmet medical and social needs leading to extraordina...

A machine learning approach for predicting suicidal thoughts and behaviours among college students.

Suicidal thoughts and behaviours are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. ...

Deep learning techniques for automated detection of autism spectrum disorder based on thermal imaging.

Children with autism spectrum disorder have impairments in emotional processing which leads to the inability in recognizing facial expressions. Since ...

Personalized machine learning of depressed mood using wearables.

Depression is a multifaceted illness with large interindividual variability in clinical response to treatment. In the era of digital medicine and prec...

Barriers and facilitators to the implementation of social robots for older adults and people with dementia: a scoping review.

BACKGROUND: Psychosocial issues, such as social isolation and loneliness among older adults and people with dementia, continue to pose challenges with...

Going deep into schizophrenia with artificial intelligence.

Despite years of research, the mechanisms governing the onset, relapse, symptomatology, and treatment of schizophrenia (SZ) remain elusive. The lack o...