Bipolar Disorder

Deep learning-based RUL and SOH prediction of lithium-ion batteries using LOCO.

Degradation in lithium-ion batteries negatively affects the reliability, safety, and cost-effectiveness of modern energy storage systems, making accurate Remaining Useful Life (RUL) prediction and State of Health (SOH) assessment essential for battery prognostics. In this work, a comprehensive comparative benchmarking framework for battery prognostics is presented using three representative deep l...

A multiscale spatio-temporal convolutional attention network for depressive disorder diagnosis via coarse-grained signal reconstruction based on EEG.

Depression disorder (DD) is a common mental disorder and a leading contributor to the global burden of disease. However, accurate diagnosis remains challenging due to the reliance of conventional approaches on subjective assessments. To address this limitation, this study proposes a Multiscale Spatio-temporal Convolutional Attention Network (MSTANet) for EEG-based depression detection. The propose...

Development and validation of an interpretable machine learning model for predicting 5-year major adverse cardiovascular events in patients with coronary artery disease.

BACKGROUND: Coronary artery disease (CAD) remains a major contributor to global cardiovascular mortality and accurate prognosis is critical for guidin...

Identification of depression types and key influencing factors among rural elderly in China: a comprehensive analysis based on machine learning and network analysis.

BACKGROUND: Depression poses a severe public health challenge for older adults, especially in rural China. In rural settings, the heavy burden of chro...

A Highly Sensitive, Ultrawide-Range Temperature-Pressure Dual-Mode Sensing Platform for Battery Health and Marine Monitoring.

Dual-mode sensors with ultrahigh sensitivity, wide detection range, linearity, and stable temperature response are highly desirable for monitoring in ...

Neuroprotective effects of Chaihu-Longgu-Muli Decoction in an insomnia-depression comorbidity model via Galectin-3-dependent JAK2/STAT3 inhibition.

ETHNOPHARMACOLOGICAL RELEVANCE: Chaihu-Longgu-Muli Decoction (CLMD) is a classical Traditional Chinese Medicine (TCM) formula from the Shanghan Lun co...

AMS-HD: Hyperdimensional Computing for Real-Time and Energy-Efficient Acute Mountain Sickness Detection.

OBJECTIVE: Acute mountain sickness (AMS) is the most prevalent altitude illness, affecting unacclimatized individuals ascending above 2,500 m and pote...

Neuroimaging studies of non-suicidal self-injury in young adults with major depressive disorder.

Non-suicidal self-injury (NSSI) is highly prevalent in adolescents with major depressive disorder (MDD), elevating suicide risk and indicating poor pr...

Shared molecular signatures linking gastroesophageal reflux disease and major depressive disorder revealed by integrated machine learning.

BACKGROUND: Gastroesophageal reflux disease (GERD) and major depressive disorder (MDD) frequently co-occur, yet their shared molecular mechanisms rema...

Towards a rational ECT treatment approach for severe and treatment resistant schizophrenia using neuroimaging biomarkers: A focused review.

Treatment resistant schizophrenia (TRS) is a major challenge in psychiatry, and its management remains an unmet need. Given the relatively high preval...

Feasibility of diagnosing major depressive disorder with a panel of serum and urine biomarkers.

BACKGROUND: Various biomarkers have been identified as being associated with the pathophysiology of major depression, with the potential to be utilise...

Heterogeneous developmental trajectories and predictors of self-harm in early adolescence: A machine learning study.

BACKGROUND: Although prior studies have examined developmental trajectories of adolescent self-harm in terms of frequency and severity, a fundamental ...

Speech as a biomarker for supported diagnosis of major depressive disorder using self-supervised representations.

The diagnosis of major depressive disorder (MDD) urgently requires objective biomarkers for clinical translation. In this study, we established a mult...

A machine-learning-derived online screening tool for depressive symptoms in chronic digestive system diseases patients: a cross-sectional study with temporal validation from CHARLS.

Chronic digestive system diseases (CDSD) are common in older adults, and depressive symptoms are associated with poorer prognosis and quality of life....

Neural abnormalities in cognitive subprocesses of emotional conflict control in bipolar II disorder: Evidence from ERPs and brain functional networks.

Patients with bipolar disorder (BD) exhibit deficits in emotional conflict control. These abnormalities may be related to alterations in distinct cogn...

On the value of radiomics in addition to clinical measures in emotional conflict fMRI for predicting sertraline response in major depressive disorder.

Most patients with major depressive disorder (MDD) do not respond to first-line treatment, and robust predictors of individual outcomes are lacking. F...

The effectiveness of CBT-based NLP-enabled AI conversational agents for mental health intervention: a systematic review and meta-analysis.

Natural language processing (NLP)-enabled artificial intelligence (AI) conversational agents (CAs) are increasingly adopted in digital mental health i...

A Chatbot for the Management of Bipolar Disorder: Using Retrieval-Augmented Generation With an Open-Weight Large Language Model to Answer Clinical Questions Based on the CANMAT and ISBD 2018 Guidelines for Bipolar Disorder: Un dialogueur pour la prise en charge du trouble bipolaire : utiliser la génération augmentée par récupération avec un grand modèle de langage (GML) à poids ouverts pour répondre aux questions cliniques fondées sur les lignes directrices de 2018 de CANMAT et de l'ISBD relatives au trouble bipolaire.

ObjectiveClinical practice guidelines support evidence-based care but are often underused due to complexity, time constraints, and navigation challeng...

Quality and readability of AI-generated information on bipolar disorder: a cross-sectional content analysis.

BACKGROUND: Bipolar disorder is a clinically sensitive and diagnostically complex condition in which unclear or incomplete psychoeducational informati...

Machine learning-based clinical tool for identifying factors associated with symptomatic knee osteoarthritis: the Nagahama study.

BACKGROUND: A clinical tool that evaluates factors associated with symptomatic knee osteoarthritis (OA) based on modifiable factors is lacking. This s...