Colorectal cancer is a very common cancer and is currently the second most common cause of death from cancer. It is a very serious cancer, and receiving proper treatment is critical. Testing for microsatellite instability (MSI), which is present in 15% of colorectal cancer cases, is currently an expensive and very time-consuming process. However, testing is necessary for these individuals, to help determine how their treatment should progress. This paper presents a deep learning algorithm to distinguish between MSI and MSS scans. It shows that by heavily compressing these types of algorithms, they can run on embedded computing systems such as a raspberry pi or a cell phone. These computing systems can be cheap and use little power. The algorithms can still retain relatively high accuracy, in this case around 80%. Colorectal deep learning algorithms have not been implemented on low power devices in prior publications.
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