Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The attempt to define toxicovigilance can be based on defining its fundamental principles: prevention of infections with toxic substances, collecting information on poisonings, both in terms of their sources and side effects, and confirming poisonings, with the aim of improving treatment. Substances referred to include both those originating from animal bites, ingested inadvertently, and those resulting from environmental poisoning in industrial regions of countries, etc. In this review, we provide information about the crucial function of poison control centres in toxicovigilance, the importance of incorporating big data analytics and artificial intelligence to streamline toxicovigilance processes, and examples of toxicovigilance in different countries. In conclusion, we will present the direction that modern toxicovigilance should take, incorporating available artificial intelligence methods to maximise efficiency.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.tox.2024.153755 | DOI Listing |
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