Machine Learning and Deep Learning Algorithms for Cancer Diagnostic Optimization

Recently, advances in machine learning and artificial intelligence have made these techniques increasingly prominent. Companies and institutions have begun investing in healthcare research to improve the accuracy of disease prediction because of its widespread popularity and effective pattern detection and categorization capabilities. However, there are numerous difficulties that arise while employing these methods. The lack of a huge data set for medical pictures is one of the biggest challenges. This study aims to provide a reasonable introduction to deep learning in medical image processing, beginning with theoretical foundations and progressing to practical implementations. Deep learning (DL) has become increasingly popular due to a number of computer science discoveries, according to a new study. To get a better grasp of neural networks, the next step was to familiarise ourselves with the principles. That’s why convolutional neural networks (CNNs) and deep learning are used. This gives us a better idea of why deep learning is advancing so quickly in so many different application domains, including medical image processing.