Bipolar Disorder

Machine Learning-Based Battery State-of-health Prediction for Unmanned Aerial Vehicles Predictive Maintenance

Battery state-of-health (SoH) prediction aims to estimate the remaining capacity by modeling battery degradation through its life cycle. Machine learning (ML)-based SoH models can accurately predict the battery remaining capacity based on voltage, current, and temperature. Battery SoH prediction for unmanned aerial vehicles (UAVs) is a crucial yet overlooked domain with data scarcity and high vari...

A 3D Brain Geometry Toolkit for Multisite Neuroimaging Analysis

Compared to traditional gross volumetrics, surface- based models provide greater spatial precision for understanding brain alterations related to developmental, neurological, and psychiatric disorders. Large-scale brain initiatives are combining data from around the world to discover and improve illness- related brain markers. Here, we present a toolkit for 3D brain geometry analysis aimed at addr...

Improving ART Retention Through Machine Learning-Guided Targeting of Interventions: A Monte Carlo Simulation Study in Lilongwe, Malawi

Retention in antiretroviral therapy care remains a major challenge in high-burden settings such as Malawi, where substantial loss to follow up undermi...

Evidence-guided AI regularization for suicidal ideation prediction in pediatric bipolar disorder

Background: Suicide prediction models in psychiatry often rely on purely data-driven feature selection, which can produce unstable and clinically opaq...

Method comparisons for differentiation of Schizophrenia and Bipolar based on rs-fMRI Intrinsic and Functional Networks

Psychosis as a symptom manifests in schizophenia and bipolar disorder, two highly heterogeneous psychiatric illnesses with overlapping clinical manife...

Identification of Direct and Network-Mediated Activation of Retinal Ganglion Cells from Visually Evoked Potentials Using Machine Learning

Objective. To preserve the encoding of visual information in prosthetic vision as close to natural as possible, subretinal photovoltaic implants, whic...

Ride, Track, and Recover: Pilot Randomized Trial of a Wearable Digital Self-Management Intervention During a Veteran Endurance-Cycling Program

Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are di...

End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS

The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conv...

Battery detection of XRay images using transfer learning

The need for detecting and sorting batteries is drastically increasing for many applications. This study proves the potential of transfer learning in ...

Neuroanatomical dimensions in recent-onset depression: clinical profiles, inflammatory markers, and proteomic ageing

Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised ...

Reproducibility of electroencephalography alpha band biomarkers for diagnosis of major depressive disorder

Major depressive disorder (MDD) and other psychiatric diseases can greatly benefit from objective decision support in diagnosis and therapy. Machine l...

Phenotypic Profiles of Suicidal Ideation in Obsessive-Compulsive Disorder: An Interpretable Machine Learning Approach

Suicidal ideation in obsessive-compulsive disorder (OCD) is common and clinically significant, yet much of the existing literature conceptualizes suic...

Eyewire II - A connectomic resource for resolving cell types and circuits of the mouse retina

Comprehensive wiring diagrams from electron microscopy (EM) are a powerful tool to understand the inner workings of the brain. The retina is an easily...

Psychological Stress-Associated Ceramide and Diacylglyceride Lipotoxicity as Contributors to First Episode Depression Pathophysiology: A neuroimmune-Metabolic-Oxidative Stress (NIMETOX) Perspective

Background: Aberrations in neuro-immune, metabolic, and oxidative stress (NIMETOX) pathways are implicated in major depressive disorder (MDD). First-e...

Cognitive Flexibility and Decision-Making in Anxiety and Depression: Meta-Analytic Evidence Facilitated by Machine-Learning Screening

The ability to adjust to changing environments (cognitive flexibility) and optimal decision-making are pivotal brain functions that govern successful ...

Advancing diagnosis of bipolar disorder using brain morphometric similarity networks in a graph AI framework

Brain similarity networks (BSNs), extracted from structural magnetic resonance imaging, provide a validated framework for studying brain network organ...

Comparison of Machine Learning Surrogate Models for Prediction of Single-Fiber Activation in Deep Brain Stimulation

Machine-learning surrogate models are positioned to help optimize deep brain stimulation (DBS) usage by predicting neural activation in response to el...

Artificial intelligence for detecting bipolar disorder in electronic health records of patients with affective diagnoses: a diagnostic accuracy study

Background: Bipolar disorder (BD) is frequently underdiagnosed, particularly in patients presenting with depressive disorders, leading to delays in ap...

Conserved neuroectodermal aging encodes primate health and longevity

Neuroectoderm-derived tissues are highly metabolically active and exhibit minimal regenerative turnover, rendering them uniquely vulnerable to age-rel...

Mixed-Precision Information Bottlenecks for On-Device Trait-State Disentanglement in Bipolar Agitation Detection

Continuous monitoring of bipolar disorder agitation via voice biomarkers requires disentangling stable speaker traits from volatile affective states o...