On medical application of neural networks trained with various types of data

Abstract

Neural networks have garnered attention over the past few years. A neural network is a typical model of machine learning that is used to identify visual patterns. Neural networks are used to solve a wide variety of problems, including image recognition problems and time series prediction problems. In addition, neural networks have been applied to medicine over the past few years. This paper classifies the ways in which neural networks have been applied to medicine based on the type of data used to train those networks. Applications of neural networks to medicine can be categorized two types: automated diagnosis and physician aids. Considering the number of patients per physician, neural networks could be used to diagnose diseases related to the vascular system, heart, brain, spinal column, head, neck, and tumors/cancer in three fields: vascular and interventional radiology, interventional cardiology, and neuroradiology. Lastly, this paper also considers areas of medicine where neural networks can be effectively applied in the future.

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