AIMC Topic: Spinal Neoplasms

Clear Filters Showing 21 to 30 of 39 articles

Development and external validation of predictive algorithms for six-week mortality in spinal metastasis using 4,304 patients from five institutions.

The spine journal : official journal of the North American Spine Society Jul 14, 2022
BACKGROUND CONTEXT: Historically, spine surgeons used expected postoperative survival of 3-months to help select candidates for operative intervention in spinal metastasis. However, this cutoff has been challenged by the development of minimally inva...
Machine Learning Algorithms Quality of Life Logistic Models Spinal Neoplasms Humans
View on PubMed DOI

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

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 Jan 28, 2022
PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system.
Humans Retrospective Studies Deep Learning Magnetic Resonance Imaging Diagnosis, Differential Spinal Neoplasms Spinal Fractures
View on PubMed DOI

Deep Learning on MRI Images for Diagnosis of Lung Cancer Spinal Bone Metastasis.

Contrast media & molecular imaging Jul 14, 2021
This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer...
Bone Neoplasms Spinal Neoplasms Humans Algorithms Prognosis Deep Learning Female Image Processing, Computer-Assisted Aged Lung Neoplasms Adult Follow-Up Studies Male Magnetic Resonance Imaging Middle Aged
View on PubMed DOI

Predicting Postoperative Mortality After Metastatic Intraspinal Neoplasm Excision: Development of a Machine-Learning Approach.

World neurosurgery Nov 16, 2020
OBJECTIVE: Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classificatio...
Humans Machine Learning Female Aged Pulmonary Disease, Chronic Obstructive Hypertension Body Mass Index Bayes Theorem Ascites Hypoalbuminemia Male Middle Aged Risk Assessment Respiration, Artificial Weight Loss Preoperative Care Laminectomy Spinal Neoplasms Dyspnea Multivariate Analysis Blood Coagulation Disorders Odds Ratio Smoking Serum Albumin Metastasectomy Mortality
View on PubMed DOI

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

International journal of radiation oncology, biology, physics May 22, 2020
PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic ...
Spinal Neoplasms Proportional Hazards Models Kaplan-Meier Estimate Life Expectancy Karnofsky Performance Status Male Middle Aged Steroids Time Factors Pelvic Bones Bone Neoplasms Area Under Curve Analgesics, Opioid Palliative Care Blood Cell Count Machine Learning Algorithms Prognosis Female Reproducibility of Results Humans
View on PubMed DOI

Single-stage posterior total en bloc spondylectomy in the treatment of lumbar spinal metastases.

Clinical neurology and neurosurgery Dec 20, 2019
OBJECTIVE: To report the clinical and radiographic outcomes of single-stage posterior total en bloc spondylectomy (TES) of lumbar spinal metastases.
Low Back Pain Metastasectomy Psoas Muscles Spinal Neoplasms Spinal Nerve Roots Lumbar Vertebrae Rectal Neoplasms Surgical Wound Infection Kidney Neoplasms Length of Stay Adult Cerebrospinal Fluid Leak Liver Neoplasms Biomechanical Phenomena Humans Pain Measurement Lung Neoplasms Male Retrospective Studies Plastic Surgery Procedures Middle Aged Blood Loss, Surgical Female Prostatic Neoplasms Postoperative Complications Operative Time Aged Neurosurgical Procedures
View on PubMed DOI

External validation of the SORG 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease.

The spine journal : official journal of the North American Spine Society Sep 7, 2019
BACKGROUND CONTEXT: Preoperative survival estimation in spinal metastatic disease helps determine the appropriateness of invasive management. The SORG ML 90-day and 1-year machine learning algorithms for survival in spinal metastatic disease were pre...
Middle Aged Survival Analysis Spinal Neoplasms Humans Machine Learning Female Aged Male
View on PubMed DOI

Random forest classifiers aid in the detection of incidental osteoblastic osseous metastases in DEXA studies.

International journal of computer assisted radiology and surgery Mar 9, 2019
PURPOSE: Dual-energy X-ray absorptiometry (DEXA) studies are used for screening patients for low bone mineral density (BMD). Patients with breast and prostate cancer are often treated with hormone-altering drugs that result in low BMD. These patients...
Lumbar Vertebrae Neoplasm Metastasis Spinal Neoplasms Absorptiometry, Photon Osteoblastoma Male Humans Middle Aged Retrospective Studies Pilot Projects Tomography, X-Ray Computed ROC Curve Female Support Vector Machine Aged
View on PubMed DOI

Shared Decision-Making Ontology for a Healthcare Team Executing a Workflow, an Instantiation for Metastatic Spinal Cord Compression Management.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Regardless of potential benefits and better outcomes, adoption of shared decision-making between a patient and providers involved in his/her care is still in its infancy. This paper intends to fill this gap by formalizing shared decision-making, situ...
Biological Ontologies Spinal Cord Compression Spinal Neoplasms Humans Patient Care Team Female Patient Participation Male Decision Making, Shared Decision Support Systems, Clinical Workflow
View on PubMed

Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.

European radiology Oct 2, 2018
OBJECTIVE: We aimed to identify optimal machine-learning methods for preoperative differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D non-enhanced computed tomography (CT) and CT-enhanced (CTE) features.
ROC Curve Imaging, Three-Dimensional Support Vector Machine Diagnosis, Differential Image Interpretation, Computer-Assisted Linear Models Spinal Neoplasms Giant Cell Tumors Sacrum Tomography, X-Ray Computed Humans Chordoma Female Machine Learning Adult Retrospective Studies Male Middle Aged
View on PubMed DOI
Popular Topics
Recent Journals