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: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
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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In silico clinical trials, particularly when augmented with artificial intelligence methods, represent an innovative approach with much to offer, particularly in the musculoskeletal field. They are a cost-effective, efficient, and ethical means of evaluating treatments and interventions by supplementing and/or augmenting traditional randomized controlled trials (RCTs). While they are not a panacea and should not replace traditional RCTs, their integration into the research process promises to accelerate medical advancements and improve patient outcomes. To accomplish this, a multidisciplinary approach is needed, and collaboration is instrumental. With advances in computing and analytical prowess, and by adhering to the tenets of team science, realization of such a novel integrative approach toward clinical trials may not be far from providing far-reaching contributions to medical research. As such, by harnessing the power of in silico clinical trials, investigators can potentially unlock new possibilities in treatment and intervention for ultimately improving patient care and outcomes.
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http://dx.doi.org/10.2106/JBJS.23.01236 | DOI Listing |