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The results indicate that convolutional neural networks (CNN) are the most widely represented when it comes to deep learning and medical image analysis. Furthermore, based on the findings of this article, it can be noted that the application of deep learning technology is widespread, but the majority of applications are focused on bioinformatics, medical diagnosis and other similar fields.<\/jats:p>","DOI":"10.3390\/mti2030047","type":"journal-article","created":{"date-parts":[[2018,8,17]],"date-time":"2018-08-17T10:54:25Z","timestamp":1534503265000},"page":"47","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":418,"title":["Deep Learning and Medical Diagnosis: A Review of Literature"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8540-2460","authenticated-orcid":false,"given":"Mihalj","family":"Bakator","sequence":"first","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d in Zrenjanin, University of Novi Sad, Djure Djakovica bb, 23000 Zrenjanin, Serbia"}]},{"given":"Dragica","family":"Radosav","sequence":"additional","affiliation":[{"name":"Technical Faculty \u201cMihajlo Pupin\u201d in Zrenjanin, University of Novi Sad, Djure Djakovica bb, 23000 Zrenjanin, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Wei, L., Yang, J., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., and Rabinovich, A. 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