AIMC Topic: Bipolar Disorder
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The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder.
Academic radiology
May 3, 2024
RATIONALE AND OBJECTIVES: To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry measurements and brain volumes using machine learning (ML) algorithms.
Machine-based learning of multidimensional data in bipolar disorder - pilot results.
Bipolar disorders
Mar 26, 2024
INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years to reach a correct diagnosis. Early recognition and early intervention might not only increase quality of life, but also increase life expectancy as ...
Comment on published article "A chat about bipolar disorder".
Bipolar disorders
Jan 18, 2024
To the Editor, we follow the topic "A chat about bipolar disorder ". According to the study's findings, ChatGPT proved its ability to deliver basic and informative information on bipolar disorders.
Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.
Journal of affective disorders
Nov 12, 2023
BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing trea...
A bidirectional thermal sensory leaky integrate-and-fire (LIF) neuron model based on bipolar NbO volatile threshold devices with ultra-low operating current.
Nanoscale
Nov 9, 2023
Brain-like artificial intelligence (AI) will become the main form and important platform in future computing. It will play an important and unique role in simulating brain functions, efficiently implementing AI algorithms, and improving computing pow...
Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study.
Journal of medical Internet research
Jul 20, 2023
BACKGROUND: Mood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early pr...
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 ...
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...
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).
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...
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