AIMC Topic: Bone Neoplasms

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Deep learning-based algorithm improved radiologists' performance in bone metastases detection on CT.

European radiology Apr 8, 2022
OBJECTIVES: To develop and evaluate a deep learning-based algorithm (DLA) for automatic detection of bone metastases on CT.
Radiologists Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Deep Learning Bone Neoplasms Algorithms Retrospective Studies Humans
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Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram.

European radiology Apr 2, 2022
OBJECTIVES: To implement a pipeline to automatically segment the ROI and to use a nomogram integrating the MRI-based radiomics score and clinical variables to predict responses to neoadjuvant chemotherapy (NAC) in osteosarcoma patients.
Neoadjuvant Therapy Magnetic Resonance Imaging Humans Osteosarcoma Bone Neoplasms Retrospective Studies Deep Learning Nomograms
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Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.

La Radiologia medica Mar 23, 2022
PURPOSE: To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI).
Retrospective Studies Reproducibility of Results Magnetic Resonance Imaging Humans Bone Neoplasms Machine Learning
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Artificial intelligence-based classification of bone tumors in the proximal femur on plain radiographs: System development and validation.

PloS one Feb 24, 2022
PURPOSE: Early detection and classification of bone tumors in the proximal femur is crucial for their successful treatment. This study aimed to develop an artificial intelligence (AI) model to classify bone tumors in the proximal femur on plain radio...
Algorithms Reproducibility of Results ROC Curve Image Processing, Computer-Assisted Humans Neural Networks, Computer Artificial Intelligence Femur Bone Neoplasms Radiography Observer Variation
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Bone Cancer Detection Using Feature Extraction Based Machine Learning Model.

Computational and mathematical methods in medicine Dec 20, 2021
Bone cancer is considered a serious health problem, and, in many cases, it causes patient death. The X-ray, MRI, or CT-scan image is used by doctors to identify bone cancer. The manual process is time-consuming and required expertise in that field. T...
Tomography, X-Ray Computed Magnetic Resonance Imaging Humans Computational Biology Bone Neoplasms Machine Learning Support Vector Machine Algorithms Image Interpretation, Computer-Assisted
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A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.

Computational and mathematical methods in medicine Nov 28, 2021
BACKGROUND: Studies focusing on prediction models are widespread in medicine. There is a trend in applying machine learning (ML) by medical researchers and clinicians. Over the years, multiple ML algorithms have been adapted to censored data. However...
Male Machine Learning Computational Biology Algorithms Osteosarcoma Computer Simulation Humans Clinical Trials as Topic Clinical Trials, Phase III as Topic Prognosis Bone Neoplasms Neural Networks, Computer Proportional Hazards Models Female Randomized Controlled Trials as Topic Data Interpretation, Statistical
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Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy.

Radiation oncology (London, England) Oct 14, 2021
OBJECTIVE: To develop high-quality synthetic CT (sCT) generation method from low-dose cone-beam CT (CBCT) images by using attention-guided generative adversarial networks (AGGAN) and apply these images to dose calculations in radiotherapy.
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Phantoms, Imaging Soft Tissue Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Humans Lung Neoplasms Neural Networks, Computer Bone Neoplasms Deep Learning Cone-Beam Computed Tomography Prognosis Tomography, X-Ray Computed
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The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study.

Journal of surgical oncology Oct 5, 2021
BACKGROUND: The prediction of survival is valuable to optimize treatment of metastatic long-bone disease. The Skeletal Oncology Research Group (SORG) machine-learning (ML) algorithm has been previously developed and internally validated. The purpose ...
Middle Aged Bone Neoplasms Extremities Female Aged Male Algorithms Retrospective Studies Humans Machine Learning
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Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.

Radiology Sep 7, 2021
Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and cla...
Humans Radiography Male Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Deep Learning Bone and Bones Female Bone Neoplasms Adult
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Automatic identification of suspicious bone metastatic lesions in bone scintigraphy using convolutional neural network.

BMC medical imaging Sep 4, 2021
BACKGROUND: We aimed to construct an artificial intelligence (AI) guided identification of suspicious bone metastatic lesions from the whole-body bone scintigraphy (WBS) images by convolutional neural networks (CNNs).
Retrospective Studies Female Humans Neural Networks, Computer Radionuclide Imaging Diagnosis, Computer-Assisted Sensitivity and Specificity Bone Neoplasms Bone and Bones Male Middle Aged
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