Predicting Scope for Survival Rate of Bone Metastases Patients with Deep Learning
Keywords:
Convolutional neural network, Deep learning, Metastasized bone tumors, Image processing, Image processingWireless sensorsAbstract
Bone cancer exists in two forms namely primary and secondary. The primary bone cancers are the ones that grow from the bone cells. The secondary bone cancers are also known as metastasized which developed from other organs and penetrated into bone. The national cancer institute states that occurrence rate of primary cancer are found to be less than 1% and the secondary forms are the most common ones in its highest rate of occurrence. Predicting the various forms of metastases bone cancer early in advance mitigates the further growth of tissues and evacuation treatment plans reduces the miserable consequences and increases the survival rate of the patient. The proposed system aims to develop a preventive kind of medical service devoted to metastasized bone cancers with a help of an improvised Convolutional Neural Network (CNN). Further the efficiency of the proposed model is investigated against the most common learning algorithms like decision tree, k-nearest neighbor (KNN), logistic regression, and random forest.
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