According to Solso (2008), artificial intelligence is a branch of computer science that uses programs to enhance cognitive functions. Pattern-recognition uses previous experience to identify a pattern accurately. Pattern-recognition through artificial intelligence is an area being explored at an extraordinary rate. Through the use of experiments using mouse brains and three data sets that consider neural networking for pattern recognition is not so far away. In the study presented by Zeng (2015), mice brains were analyzed for the gene expression patterns. This study used the Allen Developing Mouse Brain Atlas (ADA) and Allen Developing Mouse Brain Reference Atlas (ARA) along with in-situ hybridization (ISH) gene expression patterns
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Zeng 's study tested it 's experiment thousands of times and allowed for less of a margin of error (2015). Using mice as the participants does not allow for the generalization over to humans, but does pave the way for a potential experiment on humans. The terminology in this study does not allow for the layman to understand it. Outside research for the use of bag-of-words technique was needed as well as other areas of the study. Ninness 's (2012) study was reliable but used a smaller subject based. Had this study been done using one dataset would have made the study more generalized. This study was easier to understand and broke down the areas a bit better than the Zeng (2015) study. There is no comparison between the two since they are two different species being observed. Further research in pattern recognition will allow for advancement in the medical field. As shown in Ninness (2012) study, the neural network 's ability to assess breast cancer cells as its most primary stage is a huge advantage. While the use of nonhuman species is not ideal for generalization, it does allow for the hypothesis and experiments to be thoroughly researched and reliable before being considered on
Zeng 's study tested it 's experiment thousands of times and allowed for less of a margin of error (2015). Using mice as the participants does not allow for the generalization over to humans, but does pave the way for a potential experiment on humans. The terminology in this study does not allow for the layman to understand it. Outside research for the use of bag-of-words technique was needed as well as other areas of the study. Ninness 's (2012) study was reliable but used a smaller subject based. Had this study been done using one dataset would have made the study more generalized. This study was easier to understand and broke down the areas a bit better than the Zeng (2015) study. There is no comparison between the two since they are two different species being observed. Further research in pattern recognition will allow for advancement in the medical field. As shown in Ninness (2012) study, the neural network 's ability to assess breast cancer cells as its most primary stage is a huge advantage. While the use of nonhuman species is not ideal for generalization, it does allow for the hypothesis and experiments to be thoroughly researched and reliable before being considered on