Psychiatry

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

BACKGROUND: Psychosocial health issues such as depression and social isolation are an important caus...

Pattern classification as decision support tool in antipsychotic treatment algorithms.

Pattern classification aims to establish a new approach in personalized treatment. The scope is to t...

Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation.

Mental health concerns, such as suicidal thoughts, are frequently documented by providers in clinica...

Use of a tele-operated robot to increase sociability in individuals with autism spectrum disorder who display Hikikomori.

Identify abnormal functional connectivity of resting state networks in Autism spectrum disorder and apply to machine learning-based classification.

Autism spectrum disorder (ASD) patients are often reported altered patterns of functional connectivi...

Detecting neurodevelopmental trajectories in congenital heart diseases with a machine-learning approach.

We aimed to delineate the neuropsychological and psychopathological profiles of children with congen...

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.

By promising more accurate diagnostics and individual treatment recommendations, deep neural network...

Modeling anxiety and fear of COVID-19 using machine learning in a sample of Chinese adults: associations with psychopathology, sociodemographic, and exposure variables.

OBJECTIVES: Research during prior virus outbreaks has examined vulnerability factors associated with...

Mediating artificial intelligence developments through negative and positive incentives.

The field of Artificial Intelligence (AI) is going through a period of great expectations, introduci...

Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.

Previous research has studied medical professionals' perception of artificial intelligence (AI). How...

User-Centered Design of a Machine Learning Intervention for Suicide Risk Prediction in a Military Setting.

Primary care represents a major opportunity for suicide prevention in the military. Significant adva...

Conversational Agents for Chronic Disease Self-Management: A Systematic Review.

We conducted a systematic literature review to assess how conversational agents have been used to fa...

Selection of Clinical Text Features for Classifying Suicide Attempts.

Research has demonstrated cohort misclassification when studies of suicidal thoughts and behaviors (...

Using Natural Language Processing and Machine Learning to Identify Hospitalized Patients with Opioid Use Disorder.

Opioid use disorder (OUD) represents a global public health crisis that challenges classic clinical ...

Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities.

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and g...

Approaches to assessing the impact of robotics in geriatric mental health care: a scoping review.

The goals of this scoping literature review are to (1) aggregate the current research involving soci...

Identifying intentional injuries among children and adolescents based on Machine Learning.

BACKGROUND: Compared to other studies, the injury monitoring of Chinese children and adolescents has...

Let's not be indifferent about robots: Neutral ratings on bipolar measures mask ambivalence in attitudes towards robots.

Ambivalence, the simultaneous experience of both positive and negative feelings about one and the sa...

Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.

Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's dis...

Prediction of pharmacological activities from chemical structures with graph convolutional neural networks.

Many therapeutic drugs are compounds that can be represented by simple chemical structures, which co...

A natural language processing approach for identifying temporal disease onset information from mental healthcare text.

Receiving timely and appropriate treatment is crucial for better health outcomes, and research on th...