Pain Management

Enhancing Chronic Pain Nursing Diagnosis Through Machine Learning: A Performance Evaluation.

This study proposes an evaluation of the efficacy of machine learning algorithms in classifying chronic pain based on Italian nursing notes, contributing to the integration of artificial intelligence tools in healthcare within an Italian linguistic context. The research aimed to validate the nursing diagnosis of chronic pain and explore the potential of artificial intelligence (AI) in enhancing cl...

Supervised and unsupervised learning reveal heroin-induced impairments in astrocyte structural plasticity.

Astrocytes regulate synaptic activity across large brain territories via their complex, interconnected morphology. Emerging evidence supports the involvement of astrocytes in shaping relapse to opioid use through morphological rearrangements in the nucleus accumbens (NAc). However, a comprehensive assessment of astrocyte structural diversity within and between NAc subdivisions is lacking because o...

A Deep Learning Approach for Nerve Injury Classification in Brachial Plexopathies Using Magnetic Resonance Neurography with Modified Hiking Optimization Algorithm.

RATIONALE AND OBJECTIVES: Brachial plexopathies (BPs) encompass a complex spectrum of nerve injuries affecting motor and sensory function in the upper...

Enhanced glaucoma classification through advanced segmentation by integrating cup-to-disc ratio and neuro-retinal rim features.

Glaucoma is a progressive eye condition caused by high intraocular fluid pressure, damaging the optic nerve, leading to gradual, irreversible vision l...

Applying user-centred techniques and expert feedback to refine an AI-based app for addressing mobile gaming addiction in adolescents.

BACKGROUND: The prevalent use of smartphones has contributed to a rise in mobile gaming addiction, especially in young people. This study aimed to des...

Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?

In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effect...

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predict...

Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.

Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly among individuals over the age of 45. This conditi...

ConnectomeAE: Multimodal brain connectome-based dual-branch autoencoder and its application in the diagnosis of brain diseases.

BACKGROUND AND OBJECTIVE: Exploring the dependencies between multimodal brain networks and integrating node features to enhance brain disease diagnosi...

AO Spine Clinical Practice Recommendations for Diagnosis and Management of Degenerative Cervical Myelopathy: Evidence Based Decision Making - A Review of Cutting Edge Recent Literature Related to Degenerative Cervical Myelopathy.

Study DesignLiterature review of key topics related to degenerative cervical myelopathy (DCM) with critical appraisal and clinical recommendations.Obj...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic. Accurate prediction of in-hospital mortality of p...

A machine learning-based framework for predicting postpartum chronic pain: a retrospective study.

BACKGROUND: Postpartum chronic pain is prevalent, affecting many women after delivery. Machine learning algorithms have been widely used in predicting...

Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.

Diabetes is a growing global health concern, affecting millions and leading to severe complications if not properly managed. The primary challenge in ...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natur...

Identification of aging-related biomarkers for intervertebral disc degeneration in whole blood samples based on bioinformatics and machine learning.

INTRODUCTION: Aging is characterized by gradual structural and functional changes in the body over time, with intervertebral disc degeneration (IVDD) ...

Baseline predictors of responders to auricular point acupressure in chronic low back pain.

BACKGROUND: Chronic low back pain (cLBP) is a major cause of disability, with varied patient responses to treatments. Auricular point acupressure (APA...

DCATNet: polyp segmentation with deformable convolution and contextual-aware attention network.

Polyp segmentation is crucial in computer-aided diagnosis but remains challenging due to the complexity of medical images and anatomical variations. C...

Identification and Validation of Circadian Rhythm-Related Genes Involved in Intervertebral Disc Degeneration and Analysis of Immune Cell Infiltration via Machine Learning.

BACKGROUND: Low back pain is a significant burden worldwide, and intervertebral disc degeneration (IVDD) is identified as the primary cause. Recent re...

Development and validation of machine learning models for predicting post-cesarean pain and individualized pain management strategies: a multicenter study.

BACKGROUND: Effective management of postoperative pain remains a significant challenge in obstetric care due to the variability in pain perception and...

Alterations in static and dynamic functional network connectivity in chronic low back pain: a resting-state network functional connectivity and machine learning study.

Low back pain (LBP) is a prevalent pain condition whose persistence can lead to changes in the brain regions responsible for sensory, cognitive, atten...