Psychiatry

Using Unsupervised Learning to Identify Clinical Subtypes of Alzheimer's Disease in Electronic Health Records.

Identifying subtypes of Alzheimer's Disease (AD) can lead towards the creation of personalized interventions and potentially improve outcomes. In this study, we use UK primary care electronic health records (EHR) from the CALIBER resource to identify and characterize clinically-meaningful clusters patients using unsupervised learning approaches of MCA and K-means. We discovered and characterized f...

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional understanding protocol for children with autism spectrum disorders (ASD). Fourteen children (4-8 years old) were randomly assigned to 10 sessions of a cognitive behavioural therapy (CBT) intervention implemented in a group setting either with or witho...

Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning a...

An Automated Algorithm Incorporating Poincaré Analysis Can Quantify the Severity of Opioid-Induced Ataxic Breathing.

BACKGROUND: Opioid-induced respiratory depression (OIRD) is traditionally recognized by assessment of respiratory rate, arterial oxygen saturation, en...

Data-Driven Implications for Translating Evidence-Based Psychotherapies into Technology-Delivered Interventions.

Mobile mental health interventions have the potential to reduce barriers and increase engagement in psychotherapy. However, most current tools fail to...

Examining joint attention with the use of humanoid robots-A new approach to study fundamental mechanisms of social cognition.

This article reviews methods to investigate joint attention and highlights the benefits of new methodological approaches that make use of the most rec...

Depression screening using mobile phone usage metadata: a machine learning approach.

OBJECTIVE: Depression is currently the second most significant contributor to non-fatal disease burdens globally. While it is treatable, depression re...

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a mult...

Increasing the Clinical Psychiatric Knowledge Base About Pathogenic Copy Number Variation.

Specific copy number variants (CNVs) have been robustly associated with intellectual disability, autism, and schizophrenia. Most of the literature foc...

Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.

Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the patho...

Identifying Schizo-Obsessive Comorbidity by Tract-Based Spatial Statistics and Probabilistic Tractography.

A phenomenon in schizophrenia patients that deserves attention is the high comorbidity rate with obsessive-compulsive disorder (OCD). Little is known ...

Towards Precision Medicine in Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice.

In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that th...

Modeling engagement in long-term, in-home socially assistive robot interventions for children with autism spectrum disorders.

Socially assistive robotics (SAR) has great potential to provide accessible, affordable, and personalized therapeutic interventions for children with ...

Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations.

BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every ...

A Robot-Based Play-Drama Intervention May Improve the Joint Attention and Functional Play Behaviors of Chinese-Speaking Preschoolers with Autism Spectrum Disorder: A Pilot Study.

Children with autism spectrum disorder (ASD) have deficits in joint attention and play behaviors. We examined whether a robot-based play-drama interve...

Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence.

Despite the high level of interest in the use of machine learning (ML) and neuroimaging to detect psychosis at the individual level, the reliability o...

Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness.

The rapid embracing of artificial intelligence in psychiatry has a flavor of being the current "wild west"; a multidisciplinary approach that is very ...

Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses.

BACKGROUND: Digital phenotyping is the use of data from smartphones and wearables collected in situ for capturing a digital expression of human behavi...

Artificial Intelligence and the Future of Psychiatry.

An estimated 792 million people live with mental health disorders worldwide-more than one in ten people-and this number is expected to grow in the sha...

"Sorry I Didn't Hear You." The Ethics of Voice Computing and AI in High Risk Mental Health Populations.

This article examines the ethical and policy implications of using voice computing and artificial intelligence to screen for mental health conditions ...