AIMC Topic: Chordoma

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Deep-Learning-Based Model for the Prediction of Cancer-Specific Survival in Patients with Spinal Chordoma.

World neurosurgery Aug 14, 2023
OBJECTIVE: Spinal chordomas are locally aggressive and frequently recurrent tumors with a poor prognosis. Previous studies focused on a Cox regression model to predict the survival of patients with spinal chordoma. We aimed to develop a more effectiv...
Humans Deep Learning Spinal Neoplasms Chordoma Neoplasm Recurrence, Local SEER Program
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Automated Segmentation of Sacral Chordoma and Surrounding Muscles Using Deep Learning Ensemble.

International journal of radiation oncology, biology, physics Jul 13, 2023
PURPOSE: The manual segmentation of organ structures in radiation oncology treatment planning is a time-consuming and highly skilled task, particularly when treating rare tumors like sacral chordomas. This study evaluates the performance of automated...
Muscles Chordoma Humans Algorithms Deep Learning Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Synergistic drug combinations and machine learning for drug repurposing in chordoma.

Scientific reports Jul 31, 2020
Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of just 6 years and no approved medicines, the primary treatments are surgery and radiation. In order to speed new medicines to chordoma patients, a drug...
Neoplasm Proteins Pyridines Antineoplastic Combined Chemotherapy Protocols Pyrimidines Benzamides Drug Repositioning Piperazines Humans Machine Learning Cell Line, Tumor Chordoma Morpholines
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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.
Chordoma Giant Cell Tumors Sacrum Spinal Neoplasms Retrospective Studies Tomography, X-Ray Computed Female Adult Humans Machine Learning Support Vector Machine Diagnosis, Differential Image Interpretation, Computer-Assisted ROC Curve Linear Models Imaging, Three-Dimensional Male Middle Aged
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Development of Machine Learning Algorithms for Prediction of 5-Year Spinal Chordoma Survival.

World neurosurgery Aug 8, 2018
BACKGROUND: Chordomas are locally invasive slow-growing tumors that are difficult to study because of the rarity of the tumors and the lack of significant volumes of patients with longitudinal follow-up. As such, there are currently no machine learni...
Chordoma Bayes Theorem SEER Program United States Female Aged Age of Onset Machine Learning Humans Survival Analysis Algorithms Male Spinal Neoplasms Tumor Burden Middle Aged
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