AIMC Topic: Bipolar Disorder
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Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.
BMC medical informatics and decision making
Aug 2, 2024
PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for cl...
Machine learning applied to the prediction of relapse, hospitalization, and suicide in bipolar disorder using neuroimaging and clinical data: A systematic review.
Journal of affective disorders
Jun 21, 2024
BACKGROUND: Bipolar disorder (BD) is associated with increased morbidity/mortality. Adverse outcome prediction might help with the management of patients with BD.
A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.
PloS one
Jun 21, 2024
This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, ...
Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.
NeuroImage
Jun 6, 2024
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi...
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...
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