Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Simple action for depression detection: using kinect-recorded human kinematic skeletal data.

BACKGROUND: Depression, a common worldwide mental disorder, which brings huge challenges to family a...

Are social robots ready yet to be used in care and therapy of autism spectrum disorder: A systematic review of randomized controlled trials.

Autism is a neurodevelopmental disorder that affects the everyday life of people who have this lifel...

Facial Emotions Are Accurately Encoded in the Neural Signal of Those With Autism Spectrum Disorder: A Deep Learning Approach.

BACKGROUND: Individuals with autism spectrum disorder (ASD) exhibit frequent behavioral deficits in ...

Predicting women with depressive symptoms postpartum with machine learning methods.

Postpartum depression (PPD) is a detrimental health condition that affects 12% of new mothers. Despi...

A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysis.

Theoretically-driven models of suicide have long guided suicidology; however, an approach employing ...

Non-Technical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive Surgery.

Sensor technologies and data collection practices are changing and improving quality metrics across...

Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University.

There is increasing use of psychotherapy apps in mental health care. This mixed methods pilot stud...

A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis.

Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is esti...

The Prediction of Body Mass Index from Negative Affectivity through Machine Learning: A Confirmatory Study.

This study investigates on the relationship between affect-related psychological variables and Body ...

Are Surgeons Working Smarter or Harder? A Systematic Review Comparing the Physical and Mental Demands of Robotic and Laparoscopic or Open Surgery.

BACKGROUND: Minimally invasive surgical techniques such as robotic surgical platforms have provided ...

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters.

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs...

[Artificial intelligence in psychiatry: predictive value of characteristics on MR imaging of the brain].

The clinical application of neuroimaging for psychological complaints has so far been limited to the...

Applying a bagging ensemble machine learning approach to predict functional outcome of schizophrenia with clinical symptoms and cognitive functions.

It has been suggested that the relationship between cognitive function and functional outcome in sch...

"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware attention framework for relationship extraction.

With the increasing legalization of medical and recreational use of cannabis, more research is neede...

How do you feel? Using natural language processing to automatically rate emotion in psychotherapy.

Emotional distress is a common reason for seeking psychotherapy, and sharing emotional material is c...

Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach.

BACKGROUND: Mental health disorders affect multiple aspects of patients' lives, including mood, cogn...

A novel method for clinical risk prediction with low-quality data.

In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital r...

Action detection using a neural network elucidates the genetics of mouse grooming behavior.

Automated detection of complex animal behaviors remains a challenging problem in neuroscience, parti...

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Deep learning methods hold strong promise for identifying biomarkers for clinical application. Howev...

HOPES: An Integrative Digital Phenotyping Platform for Data Collection, Monitoring, and Machine Learning.

The collection of data from a personal digital device to characterize current health conditions and ...

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