학술논문

Retrieval of Large Data From Medical Lake Repository-Heart Note
Document Type
Conference
Source
2022 1st International Conference on Computational Science and Technology (ICCST) Computational Science and Technology (ICCST), 2022 1st International Conference on. :518-522 Nov, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Cloud computing
Machine learning algorithms
Scientific computing
Machine learning
Lakes
Data science
Big Data applications
Language
Abstract
The data lake was built from scratch for the size and performance of the cloud. The Azure Data Lake Store allows any company to analyze all their data in one place without any human restrictions. A data lake store can store trillions of files, and one file is 200 times larger than other cloud storages. This means that there is no need rewrite the code as the size of the stored data increases or decreases or the amount of processing power spun up increases. Data Lake also removes the complexity normally associated with big data in the cloud, enabling it to meet current and future business needs. In this project, we will create an Azure account that uses Data Lake, store electronic medical records / electronic health records (EMR / EHR) for patients, and use machine learning to classify (EMR / EHR) data types. increase. Here the KNN algorithm is used for classification to retrieve and download the data stored in the data lake. Usercan also delete the data if the user no longer needs to change the data or system.