AIMC Topic: Intervertebral Disc Displacement
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Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images.
Scientific reports
Jul 9, 2025
Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of disease. The greatest challenges today are the repetitive and time-consuming process of interpreting these complex MR images and the problem of unequal diag...
External validation of a prediction model for disability and pain after lumbar disc herniation surgery: a prospective international registry-based cohort study.
Acta orthopaedica
Jul 7, 2025
BACKGROUND AND PURPOSE: We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disability and pain 12 months after lumbar disc herniation surgery in a Swedish and Danish cohort.
Mechanisms and management of self-resolving lumbar disc herniation: bridging molecular pathways to non-surgical clinical success.
Journal of orthopaedic surgery and research
May 27, 2025
Spontaneous resorption of lumbar disk herniation (LDH) presents a promising avenue for the non-surgical management of herniated disks. Here we present a 40-year-old female with severe L5/S1 herniation who experienced spontaneous resorption confirmed ...
Machine-learning-based prediction of functional recovery in deep-pain-negative dogs after decompressive thoracolumbar hemilaminectomy for acute intervertebral disc extrusion.
Veterinary surgery : VS
Mar 25, 2025
OBJECTIVE: To develop and compare machine-learning algorithms to predict recovery of ambulation after decompressive surgery for acute intervertebral disc extrusion (IVDE).
Deep Learning for Lumbar Disc Herniation Diagnosis and Treatment Decision-Making Using Magnetic Resonance Imagings: A Retrospective Study.
World neurosurgery
Feb 26, 2025
BACKGROUND: Lumbar disc herniation (LDH) is a common cause of back and leg pain. Diagnosis relies on clinical history, physical exam, and imaging, with magnetic resonance imaging (MRI) being an important reference standard. While artificial intellige...
Development and application of AI assisted automatic reconstruction of axial lumbar disc CT images and diagnosis of lumbar disc herniation.
European journal of radiology
Feb 13, 2025
RATIONALE AND OBJECTIVES: To evaluate the value of artificial intelligence (AI) assisted diagnostic system in reconstructing axial lumbar disc CT images and diagnosing lumbar disc herniation.
WDRIV-Net: a weighted ensemble transfer learning to improve automatic type stratification of lumbar intervertebral disc bulge, prolapse, and herniation.
Biomedical engineering online
Feb 6, 2025
The degeneration of the intervertebral discs in the lumbar spine is the common cause of neurological and physical dysfunctions and chronic disability of patients, which can be stratified into single-(e.g., disc herniation, prolapse, or bulge) and com...
Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods.
Tomography (Ann Arbor, Mich.)
Dec 26, 2024
UNLABELLED: Due to the increasing number of people working at computers in professional settings, the incidence of lumbar disc herniation is increasing.
Development of a Dual-Plane MRI-Based Deep Learning Model to Assess the 1-Year Postoperative Outcomes in Lumbar Disc Herniation After Tubular Microdiscectomy.
Journal of magnetic resonance imaging : JMRI
Nov 5, 2024
BACKGROUND: Tubular microdiscectomy (TMD) is a treatment for lumbar disc herniation (LDH). Although the combination of MRI and deep learning (DL) has shown promise, its application in evaluating postoperative outcomes in TMD has not been fully explor...
Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning.
Scientific reports
Aug 20, 2024
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating th...
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