Bipolar Disorder

A Preliminary Open-Label Pilot Study of a Pillow-Based ELF-ELME (Extremely Low-Frequency, Extremely Low Magnetic Environment) Intervention for Major Depressive Disorder.

BACKGROUND: Mitochondrial dysfunction has been implicated in the pathogenesis of depression. Major depressive disorder (MDD) is a prevalent condition with substantial individual and societal burden. A novel approach-exposure to an extremely low-frequency, extremely low magnetic environment (ELF-ELME)-has shown promise. This preliminary study builds on a previous trial using a head-mounted ELF-ELME...

A hybrid CNN-DNN model for battery remaining useful life RUL prediction.

Accurate prediction of the Remaining Useful Life of lithium-ion batteries is essential for enhancing reliability, safety, and maintenance planning in energy storage systems. This study proposes an optimized hybrid deep learning framework that integrates Convolutional Neural Networks with Deep Neural Networks for effective battery remaining useful life prediction. The model leverages convolutional ...

Predicting depressive symptoms among Chinese college students using recurrent neural networks with longitudinal data.

College students face a higher risk of depression than their non-college peers. However, the predictors of depressive symptoms among college students ...

Association between fat mass index and depressive symptoms in U.S. adults: A cross-sectional analysis of NHANES 2011-2016.

Fat mass index (FMI) reflects adiposity normalized for height and may provide information beyond body mass index. Evidence on its relationship with de...

Predicting depressive symptoms in older adults with hearing impairment development and validation of NHANES-based machine-learning models: A cross-sectional study.

Depressive symptoms frequently co-occur with hearing impairment in older adults, yet available prediction tools for this high-risk subgroup remain lim...

Predict neuromuscular performance in human epidural electrical stimulation: phase 1 trial interim results.

BACKGROUND: Epidural electrical stimulation (EES) has emerged as a promising therapy for restoring motor function in patients with paralysis. A primar...

The role of biopsychosocial factors in classifying pain intensity across various chronic pain conditions.

Chronic pain is a multifaceted condition shaped by biological, psychological, and social factors, which challenges its diagnosis and treatment. While ...

Large language model empowered explainable and interpretable mental health analysis.

Concern about expressing depressive symptoms on social media is growing in the digital age. Traditional detection methods can identify depression but ...

Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

Anxiety disorders are common and impairing mental health conditions. Using data from 26,378 adults in the German National Cohort Study (NAKO), we inve...

A fully-CMOS spiking LIF neuron implementation for optimized STDP learning on memristor.

The growing demand for fast and energy-efficient computing has motivated the development of neuromorphic hardware inspired by biological neural system...

Joint trajectories of sleep duration and depressive symptoms and risk of incident multimorbidity: a longitudinal analysis with machine learning prediction.

BACKGROUND: Sleep disturbances and depressive symptoms frequently co-occur in older adults. Both conditions follow distinct, time-varying trajectories...

Displaced minds: ecologies of depression.

This issue of the Biomedical Journal explores emerging perspectives across neuropsychiatry, metabolism, aging, regenerative medicine, artificial intel...

Comment on "An exploratory study on predicting depressive symptoms in autistic individuals using wearable devices and machine learning".

Response to the comment on "An exploratory study on predicting depressive symptoms in autistic individuals using wearable devices and machine learning".

Multimodal digital phenotyping of bipolar disorder subtypes: Differences between bipolar disorder I and II based on passive and active behavioral features from smartphones.

BACKGROUND: Distinguishing between bipolar disorder type I and II constitutes a significant clinical challenge that relies on retrospective patient re...

Suicide and self-harm in the age of generative artificial intelligence: The case of ChatGPT and rise of suicide-related lawsuits.

Self-harm and suicide trends have taken a new turn in the era of GenAI and communicative chatbots. Recent OpenAI's own report suggests that 1.2 millio...

Multi-scale temporal convolution attention network for state-of-charge estimation in Li-ion batteries.

Accurate estimation of the State of Charge (SOC) in lithium-ion batteries is critical for the safety, reliability, and efficiency of energy storage sy...

From sleep staging to spindle detection: a case study on end-to-end automated sleep analysis.

Automation of sleep analysis, including both macrostructural (sleep stages) and microstructural (e.g., sleep spindles) elements, promises to enable la...

Curcumin alleviates depression-aggravated psoriasis by targeting MMP9-regulated apoptotic pathways.

Depression and psoriasis are highly comorbid, yet their shared molecular mechanisms remain poorly understood. Utilizing cross-sectional data from NHAN...

Development of an interpretable machine learning model-based online tool for risk prediction of falls and fall-related injuries in Chinese middle-aged and older adults with depressive symptoms-a longitudinal study based on the CHARLS database.

BACKGROUND: This study aimed to establish and validate interpretable Machine Learning (ML) models for predicting falls and fall-related injuries in mi...