AIMC Topic: Intervertebral Disc Degeneration

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Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect a...

Spine Explorer: a deep learning based fully automated program for efficient and reliable quantifications of the vertebrae and discs on sagittal lumbar spine MR images.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Although quantitative measurements improve the assessment of disc degeneration, acquirement of quantitative measurements relies on manual segmentation on lumbar magnetic resonance images (MRIs), which may introduce subjective bias...

Molecular basis of degenerative spinal disorders from a proteomic perspective (Review).

Molecular medicine reports
Intervertebral disc degeneration (IDD) and ligamentum flavum hypertrophy (LFH) are major causes of degenerative spinal disorders. Comparative and proteomic analysis was used to identify differentially expressed proteins (DEPs) in IDD and LFH discs co...

Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy.

PloS one
Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imagin...

Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar discectomy: feasibility of center-specific modeling.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: There is considerable variability in patient-reported outcome measures following surgery for lumbar disc herniation. Individualized prediction tools that are derived from center- or even surgeon-specific data could provide valuabl...

ISSLS PRIZE IN BIOENGINEERING SCIENCE 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologist.

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
STUDY DESIGN: Investigation of the automation of radiological features from magnetic resonance images (MRIs) of the lumbar spine.

Multi-omics identification of circulating protein biomarkers for intervertebral disc degeneration using Mendelian randomization and scRNA-seq.

Clinical rheumatology
BACKGROUND: Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear,...

Artificial intelligence assistance using deep metric learning vs. object detection in classifying lumbar disc degeneration on magnetic resonance images.

European review for medical and pharmacological sciences
UNLABELLED: OBJECTIVE: This study aimed to assess the performance of an image retrieval system based on the deep metric learning (DML) approach in discriminating between early and late stages of degenerative intervertebral disc degeneration (IDD). MA...

Identification of KCNQ1 as a diagnostic biomarker related to endoplasmic reticulum stress for intervertebral disc degeneration based on machine learning and experimental evidence.

Medicine
Intervertebral disc degeneration (IDD) is a primary cause of low back pain and disability. Cellular senescence and apoptosis due to endoplasmic reticulum stress (ERS) are key in IDD pathology. Identifying biomarkers linked to ERS in IDD is crucial fo...