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Low Back Pain

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Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

NeuroImage. Clinical
Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state ...

Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional connectivity and machine learning study.

NeuroImage. Clinical
Chronic low back pain (cLBP) is associated with widespread functional and structural changes in the brain. This study aims to investigate the resting state functional connectivity (rsFC) changes of visual networks in cLBP patients and the feasibility...

Computer Kinesiology: New Diagnostic and Therapeutic Tool for Lower Back Pain Treatment (Pilot Study).

BioMed research international
The aim of this study was to demonstrate the effectiveness of the diagnostic and therapeutic medical information system Computer Kinesiology in physiotherapy in patients with low back pain who were not responding to conventional therapy. Computer Kin...

Initial classification of low back and leg pain based on objective functional testing: a pilot study of machine learning applied to diagnostics.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment and thus provided an adjunctive dimension in patient assessment. The clinical interpretability and confounders of the 5R-STS remain poor...

Assessment and prediction of spine surgery invasiveness with machine learning techniques.

Computers in biology and medicine
BACKGROUND: The interest in Minimally Invasive Surgery (MIS) techniques has greatly increased in the recent years due to their significant advantages, both in terms of outcome improvement and cost reduction. Also in spine surgery, MIS is now applicab...

Using artificial intelligence algorithms to identify existing knowledge within the back pain literature.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Artificial intelligence algorithms can now identify hidden data patterns within the scientific literature. In 2019, these algorithms identified a thermoelectric material within the pre-2009 chemistry literature; years before its discovery in...

Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach.

Sensors (Basel, Switzerland)
Nonspecific low back pain (NSLBP) constitutes a critical health challenge that impacts millions of people worldwide with devastating health and socioeconomic consequences. In today's clinical settings, practitioners continue to follow conventional gu...

Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network.

Medical & biological engineering & computing
The paper focuses on the development of a reliable medical expert system for diagnosis of low back pain (LBP) by proposing an efficient frame-based knowledge representation scheme and a suitable resolution logic with conflicts in outcomes being resol...

A deep learning approach for lower back-pain risk prediction during manual lifting.

PloS one
Occupationally-induced back pain is a leading cause of reduced productivity in industry. Detecting when a worker is lifting incorrectly and at increased risk of back injury presents significant possible benefits. These include increased quality of li...