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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Review Purpose: The clinical management of subclinical and symptomatic varicoceles in male infertility remains challenging. Current guidelines focus on treating men with abnormal semen analyses, but a more precise approach to identify, stratify, and prognosticate men with varicoceles and fertility issues is essential.
Recent Findings: Multiple studies have utilized Artificial Intelligence (AI) to analyze clinical-demographic characteristics, semen analyses, pre-operative imaging findings, and intra-operative clinical data. These AI-driven approaches aim to discover novel biomarkers that can assess, stratify, and prognosticate men with subclinical and symptomatic varicoceles requiring early intervention. These sophisticated methodologies offer new insights and strategies for understanding normal spermatogenesis and the pathophysiology of varicocele-related male infertility. The application of AI strategies is expected to revolutionize varicocele management, enhancing male fertility and optimizing reproductive outcomes.
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http://dx.doi.org/10.1007/s11934-024-01241-5 | DOI Listing |