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Subcategories: Addictions Anxiety & Stress Bipolar Disorder Depression DSM-5 Eating Disorders Schizophrenia

Showing 2836-2856 of 5,973 articles

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

The prospective identification of children likely to develop schizophrenia is a vital tool to suppor...

Jan 2021 32310808

Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.

The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As on...

Jan 2021 33393864

Identification of autism spectrum disorder based on short-term spontaneous hemodynamic fluctuations using deep learning in a multi-layer neural network.

OBJECTIVE: To classify children with autism spectrum disorder (ASD) and typical development (TD) usi...

Dec 2020 33450566

Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

BACKGROUND: Natural language processing (NLP) tools can facilitate the extraction of biomedical conc...

Dec 2020 33380331

Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 years.

BACKGROUND: Recent studies have demonstrated that passive smartphone and wearable sensor data collec...

Dec 2020 33401123

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood.

BACKGROUND: Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease bur...

Dec 2020 33359735

Artificial neural networks for simultaneously predicting the risk of multiple co-occurring symptoms among patients with cancer.

Patients with cancer often exhibit multiple co-occurring symptoms which can impact the type of treat...

Dec 2020 33350595

Machine Learning Revealed New Correlates of Chronic Pelvic Pain in Women.

Chronic pelvic pain affects one in seven women worldwide, and there is an urgent need to reduce its ...

Dec 2020 34713065

Artificial Intelligence in mental health and the biases of language based models.

BACKGROUND: The rapid integration of Artificial Intelligence (AI) into the healthcare field has occu...

Dec 2020 33332380

Development of a Self-Harm Monitoring System for Victoria.

The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and i...

Dec 2020 33333970

A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.

BACKGROUND: Emotions after surviving cancer can be complicated. The survivors may have gained new st...

Dec 2020 33317508

Detection of eye contact with deep neural networks is as accurate as human experts.

Eye contact is among the most primary means of social communication used by humans. Quantification o...

Dec 2020 33318484

Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls.

OBJECTIVES: While theoretical models link obsessive-compulsive disorder (OCD) with executive functio...

Dec 2020 33300635

Predicting hospitalization following psychiatric crisis care using machine learning.

BACKGROUND: Accurate prediction models for whether patients on the verge of a psychiatric criseis ne...

Dec 2020 33302948

Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms.

The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactoria...

Dec 2020 33303893

Feature replacement methods enable reliable home video analysis for machine learning detection of autism.

Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million children worldwide and...

Dec 2020 33277527

Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.

IMPORTANCE: Suicide is a leading cause of death in the US. However, official national statistics on ...

Dec 2020 33355678

Using Artificial Intelligence to Predict Change in Depression and Anxiety Symptoms in a Digital Intervention: Evidence from a Transdiagnostic Randomized Controlled Trial.

While digital psychiatric interventions reduce treatment barriers, not all persons benefit from this...

Nov 2020 33278743

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Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.

Identification of autism spectrum disorder based on short-term spontaneous hemodynamic fluctuations using deep learning in a multi-layer neural network.

Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 years.

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood.

Artificial neural networks for simultaneously predicting the risk of multiple co-occurring symptoms among patients with cancer.

Machine Learning Revealed New Correlates of Chronic Pelvic Pain in Women.

Artificial Intelligence in mental health and the biases of language based models.

Development of a Self-Harm Monitoring System for Victoria.

A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.

Detection of eye contact with deep neural networks is as accurate as human experts.

Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls.

Predicting hospitalization following psychiatric crisis care using machine learning.

Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms.

Feature replacement methods enable reliable home video analysis for machine learning detection of autism.

Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.

Using Artificial Intelligence to Predict Change in Depression and Anxiety Symptoms in a Digital Intervention: Evidence from a Transdiagnostic Randomized Controlled Trial.

Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach.

Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto-Encoder Feature Representation.

Identifying individuals with autism spectrum disorder based on the principal components of whole-brain phase synchrony.

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