Machine learning methods and how they are used in medical field

Document Type:Research Paper

Subject Area:Engineering

Document 1

Data mining phases, on the other hand, refer to step-by-step processes involved during data mining. The most commonly used data mining process framework is the Cross-Industry Standard Process of Data Mining (CRISP-DM). This is an open standard that can be employed by anyone wishing to do data mining. There are six phases of data mining: Definition of the problem, Understanding data, preparing data, modeling, evaluation and deployment. Machine Learning (ML) Machine learning refers to modifications that are made to systems that are used to perform artificial Intelligence tasks. Unsupervised learning is a where an algorithm builds a mathematical model from a set of data that has only inputs and no desired output. Due to its ability to determine patterns in the data set, it is used to perform tasks such as grouping or clustering data.

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How machine learning is used in the medical field Technically, in ML the bigger the set of data the more accurate the results are likely to be. Healthcare systems all over the world are known for having huge data sets. Application of ML in this has been used to make them more effective in care delivery. For example, it has been employed by R&D in technological discoveries such as next-generation sequencing. References Abadi, M. , Barham, P. , Chen, J. , Chen, Z. Burstein, H. J. , Krilov, L. , Aragon-Ching, J. B. Jordan, M. I. , & Mitchell, T. M. Machine learning: Trends, perspectives, and prospects. Mllib: Machine learning in apache spark. The Journal of Machine Learning Research, 17(1), 1235-1241. Obermeyer, Z. , & Emanuel, E. J. R. C4.

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