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- W4205653668 abstract "This chapter describes the types and characteristics of errors in medical datasets and their impact on the quality of machine learning (ML) and methods for eliminating such mistakes. At the outset, we focus on the errors that occur when transferring information from the original medical records to the training set, with particular attention to the types of errors such as missing information. Then we consider the specifics of errors in the original medical information. Тhe final part of the chapter is devoted directly to methods of finding and preventing mistakes. Among other things, the chapter discusses an artificial intelligence (AI)-based approach for avoiding data entry errors that expert rules or statistical methods cannot detect." @default.
- W4205653668 created "2022-01-26" @default.
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- W4205653668 date "2022-01-01" @default.
- W4205653668 modified "2023-09-27" @default.
- W4205653668 title "Search and prevention of errors in medical databases" @default.
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- W4205653668 doi "https://doi.org/10.1016/b978-0-12-824521-7.00002-8" @default.
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