Bipolar Disorder (BD) is a chronic and disabling disease that usually appears around 20 to 30 years old. Patients who suffer with BD may struggle for years to achieve a correct diagnosis, and only 50% of them generally receive adequate treatment. In this work we apply a machine learning technique called Inductive Logic Programming (ILP) in order to model relapse and no-relapse patients in a first attempt in this area to improve diagnosis and optimize psychiatrists' time spent with patients. We use ILP because it is well suited for our multi-relational dataset and because a human can easily interpret the logical rules produced. Our classifiers can predict relapse cases with 92% Recall and no-relapse cases with 73% Recall. The rules and variable theories generated by ILP reproduce some findings from the scientific literature. The generated multi-relational models can be directly interpreted by clinicians and researchers, and also open space to research biological mechanisms and interventions.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Psychotic disorders, such as schizophrenia and bipolar disorder, pose significant diagnostic challenges with major implications on mental health. The measures of resting-state fMRI spatiotemporal complexity offer a powerful tool for identifying irregularities in brain activity. To capture global brain connectivity, we employed information-theoretic metrics, overcoming the limitations of pairwise correlation analysis approaches.
View Article and Find Full Text PDFBipolar disorder (BD) is characterized by temporal instability of mood and energy, but the neural correlates of this instability are poorly understood. In previous cross-sectional studies, mood state in BD has been associated with differential functional connectivity (FC) amongst several subcortical regions and ventromedial prefrontal cortex. Here, we assess whether BD is associated with longitudinal instability within this mood-related network of interest (NOI).
View Article and Find Full Text PDFPrevalence and predictors of obstructive sleep apnea in patients with bipolar disorder: A systematic review and meta-analysis.
Pak J Med Sci
January 2025
Kailong Gu Department of Geriatric Psychiatry, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Huzhou, Zhejiang Province 313000, China.
Background & Objective: Obstructive sleep apnea (OSA) has been increasingly recognized as a comorbidity in many psychiatric disorders, including bipolar disorder (BD). This study aimed to synthesize existing evidence to determine the frequency of OSA in patients diagnosed with BD and identify potential predictors of its occurrence.
Methods: PubMed, Scopus, CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar databases were searched for English-language papers published up from 1 January 1960 to 31 October 2023 that reported incidences of OSA in patients with BP and provided sufficient data for quantitative analysis.
Accidental Autoerotic Deaths and Mental Disorder: A Scoping Review.
Indian J Psychol Med
January 2025
All India Institute of Medical Sciences Bhopal, Madhya Pradesh, India.
Purpose Of The Review: Accidental autoerotic death, more commonly known as "autoerotic asphyxia," is an extreme paraphilic behavior wherein individuals induce cerebral hypoxia during self-stimulated sexual activities, often by constricting the neck or obstructing respiratory passages. Data on accidental deaths caused by autoerotic play is very low because of the non-disclosure of the mode/circumstances of death or non-paralleled forensic systems in many countries. There is a high likelihood of coexisting mental disorders with such behavior.
View Article and Find Full Text PDFChronobiologic treatments for mood disorders.
Handb Clin Neurol
January 2025
Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy.
Chronotherapeutics are nonpharmacologic interventions whose development stems from investigations into sleep and circadian rhythm abnormalities associated with mood disorder. These therapies utilize controlled exposure to environmental cues (light, darkness) to regulate biologic rhythms. They encompass sleep-wake manipulations (partial/total sleep deprivation, sleep phase adjustment) and light therapy approaches.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!