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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Artificial intelligence (AI) is rapidly transforming the landscape of obstetrics and gynaecology, offering unprecedented capabilities in diagnostics, monitoring, and personalised treatment. This review highlights the integration of AI in various domains, including obstetric imaging, fetal monitoring, gynaecologic oncology, fertility treatment, and robotic surgery. AI-powered tools are shown to enhance precision by improving diagnostic accuracy, reducing human error, and supporting clinical decision-making. Importantly, the article explores the global implications of AI adoption, including applications in low-resource settings, and emphasises the need for ethical considerations, data inclusiveness, and clinician trust. Overall, this comprehensive review demonstrates how AI is enabling more individualised and effective care in women's health.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12303583 | PMC |
http://dx.doi.org/10.7759/cureus.86929 | DOI Listing |