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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Chronic pain is a prevalent condition and the leading cause of work absenteeism worldwide. This condition involves persistent pain lasting more than three months, significantly impacting the quality of life and social interactions of patients. While the causes of chronic pain can often remain unknown, no definitive cure exists for the various known causes. Furthermore, the evaluation and prediction of pain can be challenging, particularly in unconscious patients receiving care in the intensive care unit. Subjective measures and traditional methods are typically employed for diagnosis, assessment, and treatment to identify the most effective approach. However, recent advancements in Artificial Intelligence (AI) and other computer science fields have revolutionized the medical domain, offering a novel and promising avenue for enhancing pain management. This review provides an overview of the potential benefits, limitations, and prospects associated with the role of AI in the diagnosis, assessment, and management of chronic pain.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12402416 | PMC |
http://dx.doi.org/10.31661/jbpe.v0i0.2306-1629 | DOI Listing |