AIMC Topic: Bone Neoplasms

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Sarcoma classification by DNA methylation profiling.

Nature communications
Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sa...

Deep neural network based artificial intelligence assisted diagnosis of bone scintigraphy for cancer bone metastasis.

Scientific reports
Bone scintigraphy (BS) is one of the most frequently utilized diagnostic techniques in detecting cancer bone metastasis, and it occupies an enormous workload for nuclear medicine physicians. So, we aimed to architecture an automatic image interpretin...

Effectiveness of Radiofrequency Ablation in the Treatment of Painful Osseous Metastases: A Correlation Meta-Analysis with Machine Learning Cluster Identification.

Journal of vascular and interventional radiology : JVIR
A systematic review and meta-analysis of pain response after radiofrequency (RF) ablation over time for osseous metastases was conducted in 2019. Analysis used a random-effects model with GOSH plots and meta-regression. Fourteen studies comprising 42...

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

Journal of cancer research and clinical oncology
PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient ...

Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy.

Annals of nuclear medicine
OBJECTIVE: The main aim of this work is to build a robust Convolutional Neural Network (CNN) algorithm that efficiently and quickly classifies bone scintigraphy images, by determining the presence or absence of prostate cancer metastasis.

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.

Journal of visualized experiments : JoVE
Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy exceeding its constituents. This protocol describes the development of an ML algorithm to predic...

Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application.

PloS one
Bone metastasis is one of the most frequent diseases in prostate cancer; scintigraphy imaging is particularly important for the clinical diagnosis of bone metastasis. Up to date, minimal research has been conducted regarding the application of machin...

Image based cellular contractile force evaluation with small-world network inspired CNN: SW-UNet.

Biochemical and biophysical research communications
We propose an image based cellular contractile force evaluation method using a machine learning technique. We use a special substrate that exhibits wrinkles when cells grab the substrate and contract, and the wrinkles can be used to visualize the for...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

BioMed research international
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...