Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
HIV (human immunodeficiency virus) can damage a human's immune system and cause Acquired Immunodeficiency Syndrome (AIDS) which could lead to severe outcomes, including death. While HIV infections have decreased over the last decade, there is still a significant population where the infection permeates. PrEP and PEP are two proven preventive measures introduced that involve periodic dosage to stop the onset of HIV infection. However, the adherence rates for this medication is low in part due to the lack of information about the medication. There exist several communication barriers that prevent patient-provider communication from happening. In this work, we present our ontology-based method for automating the communication of this medication that can be deployed for live conversational agents for PrEP and PEP. This method facilitates a model of automated conversation between the machine and user can also answer relevant questions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680642 | PMC |
http://dx.doi.org/10.18653/v1/2020.nlpmc-1.5 | DOI Listing |
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