Pain Management

FAMSeg: Fetal Femur and Cranial Ultrasound Segmentation Using Feature-Aware Attention and Mamba Enhancement

Accurate ultrasound image segmentation is a prerequisite for precise biometrics and accurate assessment. Relying on manual delineation introduces significant errors and is time-consuming. However, existing segmentation models are designed based on objects in natural scenes, making them difficult to adapt to ultrasound objects with high noise and high similarity. This is particularly evident in s...

YOND: Practical Blind Raw Image Denoising Free from Camera-Specific Data Dependency

The rapid advancement of photography has created a growing demand for a practical blind raw image denoising method. Recently, learning-based methods have become mainstream due to their excellent performance. However, most existing learning-based methods suffer from camera-specific data dependency, resulting in performance drops when applied to data from unknown cameras. To address this challenge...

Deep learning reveals pathology-confirmed neuroimaging signatures in Alzheimer's, vascular and Lewy body dementias.

Concurrent neurodegenerative and vascular pathologies pose a diagnostic challenge in the clinical setting, with histopathology remaining the definitiv...

Human Heterogeneity Invariant Stress Sensing

Stress affects physical and mental health, and wearable devices have been widely used to detect daily stress through physiological signals. However,...

Sheep Facial Pain Assessment Under Weighted Graph Neural Networks

Accurately recognizing and assessing pain in sheep is key to discern animal health and mitigating harmful situations. However, such accuracy is limi...

Neural Metabolic Networks: Key Elements of Healthy Brain Function.

Neural networks are responsible for processing sensory stimuli and driving the synaptic activity required for brain function and behavior. This comput...

Targeted Muscle Reinnervation and Regenerative Peripheral Nerve Interface for Myoelectric Prosthesis Control: The State of Evidence.

Prosthetic rehabilitation after amputation poses significant challenges, often due to functional limitations, residual limb pain (RLP), and phantom li...

Abnormal Static and Dynamic Functional Connectivity in Tension-Type Headache: A Support Vector Machine Analysis.

Tension-type headache (TTH) is a primary headache with the highest prevalence. Previous studies have revealed the local brain abnormalities of TTH pat...

Chinese acupoint therapies in cancer pain management: research advances and future perspectives.

Cancer pain management (CPM) is crucial in oncology care, with current approaches including pharmacotherapy, radiotherapy, chemotherapy, nerve blocks,...

Empirically Transformed Energy Patterns: A novel approach for capturing fNIRS signal dynamics in pain assessment.

The accurate assessment of pain in clinical settings is challenging due to its subjective nature. In this study, we used functional near-infrared spec...

GDP-Net: Global Dependency-Enhanced Dual-Domain Parallel Network for Ring Artifact Removal.

In Computed Tomography (CT) imaging, the ring artifacts caused by the inconsistent detector response can significantly degrade the reconstructed image...

Predicting postoperative chronic opioid use with fair machine learning models integrating multi-modal data sources: a demonstration of ethical machine learning in healthcare.

OBJECTIVE: Building upon our previous work on predicting chronic opioid use using electronic health records (EHR) and wearable data, this study levera...

Automating the Addiction Behaviors Checklist for Problematic Opioid Use Identification.

IMPORTANCE: Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Electronic health records (E...

Multidimensional Feature Analysis of Meniere's Disease and Vestibular Migraine: Insights from Machine Learning and Vestibular Testing.

OBJECTIVE: Differentiating between Meniere's disease (MD) and vestibular migraine (VM) is challenging due to overlapping symptoms and limited diagnost...

Explainable transformer-based deep survival analysis in childhood acute lymphoblastic leukemia.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common type of leukemia among children and adolescents and can be life-threatening. The inc...

Multi-level feature fusion network for kidney disease detection.

Kidney irregularities pose a significant public health challenge, often leading to severe complications, yet the limited availability of nephrologists...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issue...

Effects of an artificial intelligence-based exercise program on pain intensity and disability in patients with neck pain compared with group exercise therapy: A cohort study.

OBJECTIVES: This study compares the effects of an artificial intelligence app-based exercise program with group exercise therapy on pain intensity and...

Multi-layered data framework for enhancing postoperative outcomes and anaesthesia management through natural language processing.

Anaesthesia management is a critical aspect of perioperative care, directly influencing postoperative recovery, pain management, and patient outcomes....

Sustainable water allocation under climate change: Deep learning approaches to predict drinking water shortages.

Addressing sustainable urban water supply has become one of the most critical challenges for modern megacities, particularly in arid and semi-arid reg...