Pain Management

Designing machine learning-based models to predict residual pain after functional treatment of acute lateral ankle ligamentous sprains.

BACKGROUND: Machine learning (ML) has emerged as a transformative approach for outcome prediction in diverse disease contexts. This study sought to construct a prognostic prediction model leveraging ML algorithms and to elucidate risk factors linked to residual pain in patients with acute lateral ankle ligamentous sprains (ALALS) after functional treatment. METHODS: A total of 695 ALALS patients w...

Research progress of diffusion tensor imaging in lumbar degenerative diseases: a narrative review.

Degenerative diseases of the lumbar spine are a common cause of chronic low back pain and neurological dysfunction. Their pathological basis involves not only microscopic structural damage to the intervertebral discs but also microscopic injury to adjacent nerves and muscle tissues. Diffusion tensor imaging (DTI), which relies on the anisotropic properties of water molecule diffusion, enables non-...

Three-dimensional modeling of sensory nerve architecture and eosinophil and mast cell interactions in eosinophilic gastrointestinal disease.

Increased sensory nerve density has been described in type II inflammatory conditions and is linked to eosinophil and mast cell infiltration and neuro...

Addressing the Treatment Gap for Pediatric Headache in Underserved Regions.

PURPOSE OF REVIEW: This review explores innovative strategies to address the treatment gap for pediatric headache disorders in underserved regions wor...

Dissecting the pathobiology of suspected sepsis through a comparative analysis of endothelial inflammatory and clinical prediction models.

Sepsis remains a formidable challenge in critical care, and is characterized by profound circulatory and cellular abnormalities driven by both systemi...

NerveAI- a machine learning algorithm for detection of nerve pain in the head and neck.

Nerve pain screening in patients with headache disorders requires specialized clinical knowledge that is frequently not readily accessible at the init...

Reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.

Alterations in resting-state neural networks in subacute non-fluent aphasia after stroke: a fNIRS study.

BACKGROUND: Post-stroke aphasia is a prevalent and often disabling language impairment. Despite its high incidence, the neuropathological mechanisms u...

Propensity score-matched multicentric observational cohort study comparing robotic cholecystectomy with laparoscopic cholecystectomy.

BACKGROUND: With increasing penetration of robotic surgery, robotic cholecystectomies are becoming more popular. There are several benefits which may ...

The authors respond to reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.

Use of Generative Artificial Intelligence in the Management of Low Back Pain: a Scoping Review.

BACKGROUND CONTEXT: Low back pain (LBP) is common and a major cause of disability globally. Generative artificial intelligence (GenAI) such as ChatGPT...

Parkinson's disease severity is encoded by non-linear oscillatory interactions across cortical-subcortical networks.

Parkinson's Disease (PD) is characterized by motor symptoms linked to dysregulated neural activity within basal ganglia-thalamocortical (BGTC) circuit...

Novel machine learning fusion architectures integrating electrocardiogram representations: applications to acute coronary event detection.

AIMS: AI in electrocardiography (ECG) has diverged into two paths: traditional signal processing with machine learning, and deep learning of raw wavef...

Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.

PURPOSE: This scoping review examines current evidence supporting multimodal artificial intelligence, continuous monitoring, and digital twin concepts...

Deep Learning-based Volition Detection and Action Potential Extraction for Fully Automated Diagnosis of Neuromuscular Disease Using Needle Electromyography Signals.

OBJECTIVE: This study aimed to develop a deep learning-based volition-detection model to automate the diagnostic process and improve neuromuscular dis...

NeuroPred-GMC: a dual-branch deep learning architecture for neuropeptide prediction based on gated dilated convolutional network and multi-scale convolutional network.

Neuropeptides are multifunctional signaling molecules in the nervous system. By modulating synaptic transmission and integrating physiological systems...

Transcription Factor SPI1 Mediates Chronic Neuropathic Pain by Activating NLRC4 Transcription to Drive Microglial Activation and Inflammation.

Microglial polarization plays a key role in the process of chronic neuropathic pain (CNP). This study aims to investigate the molecular mechanism by w...

Effective real-time self-rehabilitation exercise monitoring and correctness system for low back pain management.

In the modern era of working, Musculoskeletal Disorders (MSDs) are increasing drastically. One of the leading causes of MSD is Low Back Pain (LBP). Pa...

Machine learning-based prediction of proximal junctional pathology after adult spinal deformity surgery: a systematic review and diagnostic test accuracy meta-analysis.

BACKGROUND: Proximal junctional kyphosis (PJK) and failure (PJF) remain challenging and incompletely predictable adverse event following adult spinal ...

The Ethics Committee of the Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI) - Artificial intelligence in end-of-life decision-making processes: ethical reflections.

Recent proposals to use artificial intelligence (AI) in end-of-life decision-making for incapacitated patients without advance directives have prompte...