AIMC Topic: Bipolar Disorder

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Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data.

Scientific reports Jan 9, 2023
Interpretable machine learning models for gene expression datasets are important for understanding the decision-making process of a classifier and gaining insights on the underlying molecular processes of genetic conditions. Interpretable models can ...
Bipolar Disorder Fuzzy Logic Early Detection of Cancer Gene Expression Humans Neural Networks, Computer Algorithms
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The Deep Learning Method Differentiates Patients with Bipolar Disorder from Controls with High Accuracy Using EEG Data.

Clinical EEG and neuroscience Nov 6, 2022
Bipolar disorder (BD) is a mental disorder characterized by depressive and manic or hypomanic episodes. The complexity in the diagnosis of Bipolar disorder (BD) due to its overlapping symptoms with other mood disorders prompted researchers and clini...
Algorithms Deep Learning Bipolar Disorder Electroencephalography Humans Neural Networks, Computer
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Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

Journal of affective disorders Apr 16, 2022
BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).
Decision Trees Male Humans Thyrotropin Biomarkers Depressive Disorder, Major Prealbumin Bilirubin Uric Acid Bipolar Disorder Female Triglycerides
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Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 25, 2021
Neuroimaging data driven machine learning based predictive modeling and pattern recognition has been attracted strongly attention in biomedical sciences. Machine learning based diagnosis techniques are widely applied in diagnosis of neurological dise...
Psychotic Disorders Humans Bipolar Disorder Magnetic Resonance Imaging Brain Deep Learning
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Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

PloS one Dec 31, 2020
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...
Self-Injurious Behavior Adult Humans Male Mental Health Services Adolescent Psychotic Disorders Bipolar Disorder Machine Learning Area Under Curve Suicidal Ideation Child Female Antipsychotic Agents ROC Curve Young Adult
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Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging.

Human brain mapping Nov 13, 2020
Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the abil...
Humans Machine Learning Male Deep Learning Functional Neuroimaging Adolescent Female Young Adult Adult Dorsolateral Prefrontal Cortex Executive Function Outcome Assessment, Health Care Magnetic Resonance Imaging Bipolar Disorder Psychomotor Performance Schizophrenia Support Vector Machine Follow-Up Studies
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Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.

Personalized medicine Oct 30, 2020
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized ...
Depressive Disorder, Major Big Data Bipolar Disorder Schizophrenia Humans Machine Learning Metabolomics Early Diagnosis Remote Sensing Technology Mental Disorders
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A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach.

Progress in neuro-psychopharmacology & biological psychiatry Oct 9, 2020
BACKGROUND: Mood disorders (major depressive disorder, MDD, and bipolar disorder, BD) are considered leading causes of life-long disability worldwide, where high rates of no response to treatment or relapse and delays in receiving a proper diagnosis ...
Male Middle Aged Bipolar Disorder Depressive Disorder Inflammation Diagnosis, Differential Biomarkers Female Humans Adult Machine Learning Cytokines
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Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning.

Molecular psychiatry Oct 1, 2020
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurob...
Bipolar Disorder Magnetic Resonance Imaging Brain Depressive Disorder, Major Deep Learning Humans
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A deep learning model for detecting mental illness from user content on social media.

Scientific reports Jul 16, 2020
Users of social media often share their feelings or emotional states through their posts. In this study, we developed a deep learning model to identify a user's mental state based on his/her posting information. To this end, we collected posts from m...
Deep Learning Depression Bipolar Disorder Semantics Autistic Disorder Social Media Schizophrenia Adult Mental Health Male Anxiety Humans Psycholinguistics Phonetics Female Borderline Personality Disorder Blogging
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