Prediction of Osteosarcoma Using Binary Convolutional Neural Network: A Machine Learning Approach

This study explores the use of Convolutional Neural Networks (CNN) for predicting osteosarcoma, a challenging bone cancer. Leveraging CNN's efficacy in medical image analysis, the research develops a specialized prediction model. The dataset, featuring diverse raw images from various medical imaging techniques, ensures a representative case spectrum. Pre-processing techniques like resizing, normalization, and augmentation optimize the dataset for effective CNN training. Through systematic partitioning into training and testing sets, the study comprehensively evaluates the CNN model's performance in osteosarcoma prediction. This research contributes valuable insights into CNN's role in bone cancer prediction, highlighting its effectiveness in navigating the complexities of osteosarcoma detection, thereby advancing accuracy in medical diagnoses.