Kitap bölümü Açık Erişim
Abut,Serdar;
Okut, Hayrettin;
Zackula,Rosey;
Kallail,Ken James
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<subfield code="a"><p>Artificial Intelligence (AI) has played a significant role in improving decision-making within the healthcare system. AI includes machine learning, which encompasses a subset called artificial neural networks (ANNs). These networks mimic how biological neurons in the brain signal one another. In this chapter, we conduct a seminal review of ANNs and explain how prediction and classification tasks can be conducted in the field of medicine. Basic information is provided showing how neural networks solve the problem of determining disease subsets by analyzing huge amounts of structured and unstructured patient data. We also provide information on the application of conventional ANNs and deep convolutional neural networks (DCNNs) that are specific to medical image processing. For example, DCNNs can be used to detect the edges of an item within an image. The acquired knowledge can then be transferred so that similar edges can be identified on another image. This chapter is unique; it is specifically aimed at medical professionals who are interested in artificial intelligence. Because we will demonstrate the application in a straightforward manner, researchers from other technical fields will also benefit.</p></subfield>
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<subfield code="t">Deep Learning - Recent Findings and Research</subfield>
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<subfield code="a">The authors would like to thank University of Kansas School of Medicine-Wichita for financial support.</subfield>
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