AIMC Topic: Neck Pain

Clear Filters Showing 1 to 10 of 14 articles

Machine learning analysis of kinematic movement features during functional tasks to discriminate chronic neck pain patients from asymptomatic controls.

Scientific reports
This study evaluated the discriminative potential of a machine learning model using movement features during functional tasks to distinguish between patients with non-traumatic chronic neck pain and asymptomatic controls. The study included patients ...

Multi-modal and Multi-view Cervical Spondylosis Imaging Dataset.

Scientific data
Multi-modal and multi-view imaging is essential for diagnosis and assessment of cervical spondylosis. Deep learning has increasingly been developed to assist in diagnosis and assessment, which can help improve clinical management and provide new idea...

[Population screening for acupuncture treatment of neck pain: a machine learning study].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
OBJECTIVE: To screen the population for acupuncture treatment of neck pain, using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms.

NABNet: Deep Learning-Based IoT Alert System for Detection of Abnormal Neck Behavior.

Sensors (Basel, Switzerland)
The excessive use of electronic devices for prolonged periods has led to problems such as neck pain and pressure injury in sedentary people. If not detected and corrected early, these issues can cause serious risks to physical health. Detectors for g...

An Artificial Intelligence-Based App for Self-Management of Low Back and Neck Pain in Specialist Care: Process Evaluation From a Randomized Clinical Trial.

JMIR human factors
BACKGROUND: Self-management is endorsed in clinical practice guidelines for the care of musculoskeletal pain. In a randomized clinical trial, we tested the effectiveness of an artificial intelligence-based self-management app (selfBACK) as an adjunct...

Factors influencing the use of an artificial intelligence-based app (selfBACK) for tailored self-management support among adults with neck and/or low back pain.

Disability and rehabilitation
PURPOSE: Tailored self-management support is recommended as first-line treatment for neck and low back pain, for which mHealth applications could be promising. However, there is limited knowledge about factors influencing the engagement with such app...

Utilizing machine learning to predict post-treatment outcomes in chronic non-specific neck pain patients undergoing cervical extension traction.

Scientific reports
This study explored the application of machine learning in predicting post-treatment outcomes for chronic neck pain patients undergoing a multimodal program featuring cervical extension traction (CET). Pre-treatment demographic and clinical variables...

Unsupervised machine learning for clustering forward head posture, protraction and retraction movement patterns based on craniocervical angle data in individuals with nonspecific neck pain.

BMC musculoskeletal disorders
OBJECTIVES: The traditional understanding of craniocervical alignment emphasizes specific anatomical landmarks. However, recent research has challenged the reliance on forward head posture as the primary diagnostic criterion for neck pain. An advance...

Machine learning models for classifying non-specific neck pain using craniocervical posture and movement.

Musculoskeletal science & practice
OBJECTIVE: Physical therapists and clinicians commonly confirm craniocervical posture (CCP), cervical retraction, and craniocervical flexion as screening tests because they contribute to non-specific neck pain (NSNP). We compared the predictive perfo...

Automatic literature screening using the PAJO deep-learning model for clinical practice guidelines.

BMC medical informatics and decision making
BACKGROUND: Clinical practice guidelines (CPGs) are designed to assist doctors in clinical decision making. High-quality research articles are important for the development of good CPGs. Commonly used manual screening processes are time-consuming and...