Published Paper Details:

CNNs, or Convolutional Neural Networks, are an advanced type of neural network that processes data, specifically images, using deep learning algorithms. The use of CNNs is expanding rapidly, especially in the healthcare field, as research in deep learning advances. Cancer is a devastating disease that has claimed numerous lives worldwide, and early detection is crucial to determine whether the disease is curable or becomes critical. Bone cancer, which is characterized by abnormal tissue growth, can spread to other parts of the body. There are two types of bone cancer: cancerous and non-cancerous, with the latter being curable. Medical equipment such as CT scans, MRI scans, and X-rays are used to detect bone cancer. Early cancer detection is crucial in cases of metastasis, which is a non-curable disease. This paper aims to analyze and study the potential of Convolutional Neural Networks (CNN) in the early detection of bone cancer. By comparing various existing approaches and analyzing their effectiveness, this paper will highlight the potential of CNN algorithms in comparative analysis with their performance