Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Healthcare systems capture patients' data using different medical equipment and store it in the databases with a continual increase in data volume. The continuous processing and sharing of this massive data are rising concerns in live data transferring over the networks. Sending patient data to the distant remote user without proper compressing format requires high latency in the communication channels. Any alternation of data transmitted via the communication medium may also cause issues in assuring data authentication and integrity. For solving the problems, watermarking method is being applied to ensure such security, which has a cheaper computational cost. Various watermarking mechanisms are available for ensuring health data security, especially for medical images. Watermarking on the text was not used yet due to the lack of efficient technique. This paper proposes a secured compression technique for patient live-text data while sharing them remotely over a bandwidth-deficient channel. To test the proposed system, we use patient data. The result indicates that the proposed strategy outperforms the existing compression methods and is robust enough to provide data integrity and authentication.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9529588 | PMC |
http://dx.doi.org/10.1016/j.heliyon.2022.e10788 | DOI Listing |