ANALYSIS OF MEDICAL IMAGES (X-RAY, CT, MRI) BASED ON MACHINE LEARNING
DOI:
https://doi.org/10.55640/Keywords:
Data Mining, medical images, X-ray diagnostics, MRI analysis, machine learning, image processing, artificial intelligence, medical diagnostics.Abstract
In modern medicine, automating diagnostic processes and improving detection quality is a pressing issue. This thesis examines methods for analyzing medical images, specifically X-ray and magnetic resonance imaging (MRI) results, using Data Mining technologies. The possibilities of detecting diseases at early stages, improving diagnostic accuracy, and supporting physicians in the decision-making process through data mining technologies are analyzed.
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References
1.Kumar, V., et al. Introduction to Data Mining. Addison Wesley, 2022.
2.Litjens, G., et al. "A Survey on Deep Learning in Medical Image Analysis." Medical Image Analysis, 2017.
3.LeCun, Y., Bengio, Y., Hinton, G. "Deep Learning." Nature, 2015.
4.Kermany, D., et al. "Identifying Medical Diagnoses from Images with Deep Learning." Cell, 2018.
5.Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. MIT Press, 2016.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.
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