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Efficiency and Scalability Methods in Cancer Detection Problems
Abstract
Computer aided detection (CAD) system for cancer detection from X-ray images is highly requested by radiologists. For CAD systems to be successful, a large amount of data has to be collected. This poses new challenges for developing learning algorithms that are efficient and scalable to large dataset sizes. One way to achieve this efficiency is by using good feature selection.
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