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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As the aging process accelerates, the incidence of chronic diseases in the elderly is rising. As a result, it is crucial to optimize health education for the elderly. Pulmonary aspiration and aspiration pneumonia are significant concerns endangering the health of the elderly. The health education paradigm now in use to prevent pulmonary aspiration in the elderly has numerous flaws, including a lack of home-based health education and the digital divide. Large language model (LLM), an example of artificial intelligence technology, is anticipated to bring a chance to address these issues and offer easily comprehensible health information for the prevention of pulmonary aspiration in the elderly. Our multidisciplinary research team fully understood the needs from the perspective of physicians, nurses and patients, built a knowledge graph (KG), and developed an intelligent Health EducAtion system based on LLM for the prevention of elderly Pulmonary Aspiration (iHEAL-ePA system).
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http://dx.doi.org/10.3233/SHTI240141 | DOI Listing |