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- W4307647879 abstract "AbstractHealth care is one of the fast-growing industries. It is among the foremost well-known divisions within the world where the information created from such industries is extremely huge in volume. It generates relevant healthcare data, including medical images, as part of the healthcare information system (HIS). This data can be used for current and future decision-making of some clinical aspects; it can be sometimes real time too. Moreover, presenting an image in real time can be very challenging. In this way, a legitimate reinforcement is required to preserve for such valuable information so that it can be reestablish at the time of prerequisite. This huge data of medical industry are hard to store and recover at the time of requirement. Keeping the earlier research in observation, few strategies are presented in this paper which centers on the diverse strategies that can be utilized to store the medical images utilizing NoSQL database which are considered the leading to store expansive volume of information.KeywordsBackupLarge datasetsMedical imagesDICOMMongoDBNoSQL databaseRecoveryStorage" @default.
- W4307647879 created "2022-11-04" @default.
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- W4307647879 date "2022-10-28" @default.
- W4307647879 modified "2023-09-27" @default.
- W4307647879 title "Backup and Restore Strategies for Medical Image Database Using NoSQL" @default.
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- W4307647879 doi "https://doi.org/10.1007/978-981-19-4990-6_15" @default.
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