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Spinal Stenosis

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Rule-based Cervical Spine Defect Classification Using Medical Narratives.

Studies in health technology and informatics 26262337
Classifying the defects occurring at the cervical spine provides the basis for surgical treatment planning and therapy recommendation. This process requires evidence from patient records. Further, the degree of a defect needs to be encoded in a stand...
Algorithms Biological Ontologies Cervical Vertebrae Decision Support Systems, Clinical Diagnosis, Computer-Assisted Electronic Health Records Humans Knowledge Bases Machine Learning Narration Natural Language Processing Reproducibility of Results Sensitivity and Specificity Spinal Stenosis Terminology as Topic
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Monitoring the quality of robot-assisted pedicle screw fixation in the lumbar spine by using a cumulative summation test.

Spine 25575085
STUDY DESIGN: Prospective randomized controlled trial.
Adult Aged Aged, 80 and over Female Humans Lumbar Vertebrae Male Middle Aged Minimally Invasive Surgical Procedures Pedicle Screws Robotics Spinal Fusion Spinal Stenosis Treatment Outcome
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Gait Analysis Using a Support Vector Machine for Lumbar Spinal Stenosis.

Orthopedics 26558674
Lumbar spinal canal stenosis (LSS) is diagnosed based on physical examination and radiological documentation of lumbar spinal canal narrowing. Differential diagnosis of the level of lumbar radiculopathy is difficult in multilevel spinal stenosis. The...
Aged Aged, 80 and over Ankle Joint Case-Control Studies Female Gait Humans Knee Joint Lumbar Vertebrae Male Middle Aged Radiculopathy Spinal Stenosis Support Vector Machine Walking
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Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

Medical image analysis 27816860
As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to t...
Algorithms Humans Magnetic Resonance Imaging Spinal Canal Spinal Stenosis Unsupervised Machine Learning
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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 28168339
STUDY DESIGN: Investigation of the automation of radiological features from magnetic resonance images (MRIs) of the lumbar spine.
Bone Marrow Humans Intervertebral Disc Intervertebral Disc Degeneration Lumbar Vertebrae Magnetic Resonance Imaging Male Middle Aged Neural Networks, Computer Radiologists Spinal Stenosis Spondylolisthesis
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Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

Neuroinformatics 29450848
Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automa...
Aged Female Humans Intervertebral Disc Degeneration Lumbar Vertebrae Machine Learning Male Middle Aged Multitasking Behavior Neural Networks, Computer Spinal Nerve Roots Spinal Stenosis
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Qualitative versus quantitative lumbar spinal stenosis grading by machine learning supported texture analysis-Experience from the LSOS study cohort.

European journal of radiology 31005175
PURPOSE: To investigate and compare the reproducibility and accuracy of qualitative ratings and quantitative texture analysis (TA) in detection and grading of lumbar spinal stenosis (LSS) in magnetic resonance imaging (MR) scans of the lumbar spine.
Aged Aged, 80 and over Algorithms Cohort Studies Female Humans Lumbar Vertebrae Machine Learning Magnetic Resonance Imaging Male Middle Aged Observer Variation Outcome Assessment, Health Care Reference Standards Reproducibility of Results Spinal Stenosis
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Predicting discharge placement after elective surgery for lumbar spinal stenosis using machine learning methods.

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 30941521
PURPOSE: An excessive amount of total hospitalization is caused by delays due to patients waiting to be placed in a rehabilitation facility or skilled nursing facility (RF/SNF). An accurate preoperative prediction of who would need a RF/SNF place aft...
Aged Algorithms Elective Surgical Procedures Female Humans Lumbar Vertebrae Machine Learning Male Middle Aged Netherlands Neural Networks, Computer Patient Discharge Patient Transfer Postoperative Care Predictive Value of Tests Quality Improvement Rehabilitation Centers Skilled Nursing Facilities Spinal Stenosis
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Machine learning-based preoperative predictive analytics for lumbar spinal stenosis.

Neurosurgical focus 31042660
OBJECTIVEPatient-reported outcome measures (PROMs) following decompression surgery for lumbar spinal stenosis (LSS) demonstrate considerable heterogeneity. Individualized prediction tools can provide valuable insights for shared decision-making. The ...
Aged Algorithms Decompression, Surgical Feasibility Studies Female Humans Length of Stay Lumbar Vertebrae Machine Learning Male Middle Aged Predictive Value of Tests Recovery of Function Retrospective Studies Spinal Stenosis Treatment Outcome
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