Pain Management

Forecasting the development trend of the green finance market based on long short-term memory and transformer models.

With the continuous development of the global green finance market, accurately forecasting its trends has become a critical issue in financial research. Traditional time series forecasting methods are commonly used in this domain, but when applied to complex green finance data, they often suffer from low robustness, weak generalization ability, and difficulty in simultaneously capturing global tre...

From molecular mechanisms to digital surveillance: the 2010-2025 evolution of benzodiazepine and Z-drug misuse research.

The misuse of benzodiazepines (BZDs) and Z-drugs poses significant global public health challenges. This study maps the scientific evolution and paradigm shifts in this field from 2010 to 2025. A bibliometric analysis of 6,311 publications from the Web of Science Core Collection was performed using VOSviewer and CiteSpace to identify collaboration networks, research hotspots, and emerging frontier...

Machine learning-based cross-sectional exploration of depression-chronic pain associations in chronic respiratory disease patients.

BACKGROUND: Chronic respiratory diseases (CRD) are a leading global cause of death, with high comorbidity rates of depression and chronic pain forming...

An intelligent wearable insole system for machine learning-based detection of high-risk postures in static symmetrical load-lifting tasks.

Work-related musculoskeletal disorders (WMSDs) remain a major occupational health concern worldwide, with manual material handling, particularly lifti...

Artificial intelligence in headache care.

Orchestrator multi-agent clinical decision support system for secondary headache diagnosis in primary care.

OBJECTIVE: Secondary headaches require urgent recognition due to potentially devastating consequences if untreated. Despite established clinical "red ...

Cognitive gains and addictive losses: The double-edged sword of Generative AI on employee creative thinking.

Drawing on Social Cognitive Theory (SCT), this study examines how Generative Artificial Intelligence (GAI) use is associated with employee creative th...

Development of high-precision automated dynamic plantar aesthesiometer (ADPA): a promising tool in pain research.

Chronic pain is a severe burden affecting 20% of the population worldwide. To develop novel analgesics, in vivo preclinical assessment of the pain thr...

Machine learning classification and regional differentiation of neuropathologically-confirmed Alzheimer's disease and comorbid Lewy body disease.

BACKGROUND: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) co-occur frequently, and growing evidence, including neuropathology, supports...

Consistent analgesic effect of intravenous dexamethasone on rebound pain after brachial plexus block: a causal machine learning approach.

BACKGROUND: Rebound pain, a sudden increase in pain intensity after resolution of regional anesthesia, remains a major challenge in postoperative pati...

Retraction Note: Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality.

First-Pass Reperfusion After Endovascular Thrombectomy: A Real-World Analysis with Explainable Machine Learning for Intra-Procedural Decision Support.

OBJECTIVE: To evaluate determinants of first-pass reperfusion and to develop an explainable machine learning framework for intra-procedural decision s...

LumbarSR: A Paired Clinical CT and Photon-Counting Micro-CT Dataset for Human Lumbar Vertebrae.

Low back pain affects hundreds of millions of people and is associated with degenerative changes in the lumbar spine. Trabecular bone microarchitectur...

Risk prediction models based on machine learning for emergence delirium in elderly patients undergoing spine surgery: development and validation study.

BACKGROUND: Emergence delirium (ED) is a common complication in elderly patients undergoing surgery for degenerative spinal disease (DSD) and is assoc...

Hybrid deep learning for mental workload classification using EEG with enhanced preprocessing and interpretability.

Mental workload classification is critical in safety-sensitive fields such as healthcare and aviation. However, electroencephalography-based approache...

[An electroencephalogram-based emotion recognition method using multi-branch convolutional neural networks and Transformer].

Electroencephalogram (EEG)-based emotion recognition is an important research area in affective computing and mental health assessment. To address the...

Reinforcement learning-driven adaptive game therapy for cognitive impairment patients with improved vision transformer based detection model.

BACKGROUND: Cognitive impairment is the growing challenge that requires early diagnosis and personalized management of neurodegenerative conditions li...

3DTMC-LLM: A 3D Geometry-Aware Large Language Model for Transition Metal Complexes.

Large language models (LLMs) have demonstrated remarkable reasoning capabilities across various natural language tasks. However, comparable breakthrou...

Enhancing enterprise decision support via swin transformer-based OCR-free information extraction.

Extracting key information from vast amounts of documents and data plays a crucial role in knowledge graph construction, intelligence analysis, decisi...

Behavioral patterns in iGaming across territories: Psychiatric and AI-driven insights via the internet of behavior.

BackgroundIn the digital era, iGaming has become a rapidly expanding phenomenon that generates complex behavioral patterns and increases the risk of p...