AIMC Topic: Osteosarcoma
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Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.
Contrast media & molecular imaging
Jul 24, 2019
PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical intervention. Response to chemotherapy, however, is affected by intratumor heterogeneity. In this study, we assessed the ability of a machine learning ...
Screening of disorders associated with osteosarcoma by integrated network analysis.
Bioscience reports
May 21, 2019
Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation networ...
Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.
PloS one
Apr 17, 2019
Pathological estimation of tumor necrosis after chemotherapy is essential for patients with osteosarcoma. This study reports the first fully automated tool to assess viable and necrotic tumor in osteosarcoma, employing advances in histopathology digi...
Robotic Patterning a Superhydrophobic Surface for Collective Cell Migration Screening.
Tissue engineering. Part C, Methods
Mar 27, 2018
Collective cell migration, in which cells migrate as a group, is fundamental in many biological and pathological processes. There is increasing interest in studying the collective cell migration in high throughput. Cell scratching, insertion blocker,...
Assessing microscope image focus quality with deep learning.
BMC bioinformatics
Mar 15, 2018
BACKGROUND: Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with hig...
Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.
Journal of computational biology : a journal of computational molecular cell biology
Oct 30, 2017
Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a ...
A support vector machine classifier for the prediction of osteosarcoma metastasis with high accuracy.
International journal of molecular medicine
Sep 7, 2017
In this study, gene expression profiles of osteosarcoma (OS) were analyzed to identify critical genes associated with metastasis. Five gene expression datasets were screened and downloaded from Gene Expression Omnibus (GEO). Following assessment by M...
Effect of Short-Term Stimulation with Interleukin-1β and Differentiation Medium on Human Mesenchymal Stromal Cell Paracrine Activity in Coculture with Osteoblasts.
BioMed research international
Dec 22, 2015
INTRODUCTION: Human mesenchymal stromal cells (hMSCs) exhibit the potential to accelerate bone healing by enhanced osteogenic differentiation. Interleukin-1β is highly expressed during fracture healing and has been demonstrated to exert a significant...
Microfluidics-based label-free SERS profiling of exosomes with machine learning for osteosarcoma diagnosis.
Talanta
Nov 1, 2025
Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze ...
Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.
Clinical imaging
Jul 1, 2025
BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant chemotherapy (NAC) improves survival rates. However, OS heterogeneity results in variable treatment responses, highlighting the need for reliable, non-...
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