Psychiatry

Bipolar Disorder

Latest AI and machine learning research in bipolar disorder for healthcare professionals.

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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.

Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and ...

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment...

Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.

Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessm...

Specific heat anomalies and local symmetry breaking in (anti-)fluorite materials: A machine learning molecular dynamics study.

Understanding the high-temperature properties of materials with (anti-)fluorite structures is crucia...

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.

BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable ma...

Gray Matter Differences in Adolescent Psychiatric Inpatients: A Machine Learning Study of Bipolar Disorder and Other Psychopathologies.

BACKGROUND: Bipolar disorder (BD) is among the psychiatric disorders most prone to misdiagnosis, wit...

HEDL: Deep learning multiple approaches for early detection of depression using sarcastic text.

Sarcasm is particularly notorious towards mental health, and thus it is quite essential for early id...

Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major D...

Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.

Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and inf...

Effect of Cumulative Exposure on the Efficacy of Paroxetine: A Population Pharmacokinetic-Pharmacodynamic and Machine Learning Analyses.

Selective serotonin reuptake inhibitors (SSRIs) are widely used in depression treatment. However, th...

A novel framework for seasonal affective disorder detection: Comprehensive machine learning analysis using multimodal social media data and SMOTE.

Seasonal Affective Disorder (SAD) is a mood disorder characterized by recurring depressive episodes ...

Advances in EEG-based detection of Major Depressive Disorder using shallow and deep learning techniques: A systematic review.

The contemporary diagnosis of Major Depressive Disorder (MDD) primarily relies on subjective assessm...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and c...

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized cl...

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study.

BACKGROUND: Conventional approaches for major depressive disorder (MDD) screening rely on two effect...

Accurate Prediction of Open-Circuit Voltages of Lithium-Ion Batteries via Delta Learning.

Accurate prediction of lithium-ion battery capacity before material synthesis is crucial for acceler...

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