Optimization of Pediatric Cancer Diagnosis with Convolutional Neural Networks (CNNs)

Abstract

In today’s world, technology has become much more prevalent in the world of medicine. Growing fields like biotechnology and artificial intelligence are helping save and improve lives in ways that we couldn’t have imagined just 40, 50 years ago. Some of the most common examples of this today are prosthetics and using artificial intelligence in radiology. In the past few years, artificial intelligence technology has been advancing and scientists have begun to research whether deep learning algorithms like convolutional neural networks can be used to help detect signs of and diagnose cancer. Specifically, a growing research field refers to using deep learning and CNN models to detect pediatric cancer, one of the hardest cancers to detect based on symptoms. In this paper, it will be discussed whether deep learning algorithms are effective in use for the detection or diagnosis of pediatric cancers.