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Low Back Pain

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Da Vinci Meets Globus Excelsius GPS: A Totally Robotic Minimally Invasive Anterior and Posterior Lumbar Fusion.

World neurosurgery
BACKGROUND: Minimally invasive approaches to the spine via anterior and posterior approaches have been increasing in popularity, culminating in the development of robot-assisted spinal fusions. The da Vinci surgical robot has been used for anterior l...

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

PloS one
BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and socio-economic implications. The predominant form is non-specific LBP (NSLBP), lacking treatable pathology. Active physical interventions tailored to in...

Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire.

Computers in biology and medicine
BACKGROUND: Health-related patient-reported outcomes (HR-PROs) are crucial for assessing the quality of life among individuals experiencing low back pain. However, manual data entry from paper forms, while convenient for patients, imposes a considera...

Dynamic assessment of spine movement patterns using an RGB-D camera and deep learning.

Journal of biomechanics
In clinical practice, functional limitations in patients with low back pain are subjectively assessed, potentially leading to misdiagnosis and prolonged pain. This paper proposes an objective deep learning (DL) markerless motion capture system that u...

Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality.

La Radiologia medica
INTRODUCTION: Low back pain is a global health issue causing disability and missed work days. Commonly used MRI scans including T1-weighted and T2-weighted images provide detailed information of the spine and surrounding tissues. Artificial intellige...

Machine Learning Models for Low Back Pain Detection and Factor Identification: Insights From a 6-Year Nationwide Survey.

The journal of pain
This study aimed to enhance performance, identify additional predictors, and improve the interpretability of biopsychosocial machine learning models for low back pain (LBP). Using survey data from a 6-year nationwide study involving 17,609 adults age...

The Success of Deep Learning Modalities in Evaluating Modic Changes.

World neurosurgery
BACKGROUND: Modic changes are pathologies that are common in the population and cause low back pain. The aim of the study is to analyze the modic changes detected in magnetic resonance imaging (MRI) using deep learning modalities.

Machine learning-based automated scan prescription of lumbar spine MRI acquisitions.

Magnetic resonance imaging
PURPOSE: High quality scan prescription that optimally covers the area of interest with scan planes aligned to relevant anatomical structures is crucial for error-free radiologic interpretation. The goal of this project was to develop a machine learn...

Mo-fi-disc scoring system: Towards understanding the radiological tools to better delineate the disease process and enhancing our solutions for low back pain in artificial intelligence era.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
BACKGROUND: 'Mo-fi-disc' is a new scoring system that quantifies degeneration of the lumbar spine and predicts the intensity of low back pain (LBP). However, its association with LBP-related disability is unknown. In the present study, we aimed to an...