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Colorectal cancer (CRC) is the second most dangerous type of cancer in terms of causing deaths in patients and third most common type of cancer found in people in terms of incidence. CRC can be further categorized based on its molecular subtypes. Each subtype displays different features. Thus, identifying molecular subtypes of CRC and treating patients accordingly can help achieve better therapeutic results rather than providing the same treatment for all colorectal cancer patients. Our research aims at identifying molecular subtypes of colorectal cancer using gene expression data by building a model using some machine learning and deep learning algorithms.

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machine-learning colon-cancer clustering dimensionality-reduction

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