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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We applied machine learning techniques to build models that predict perceived risks and benefits of using artificial intelligence (AI) algorithms to recruit African American informal caregivers for clinical trials and general health disparity research via social media platforms. In a U.S. sample of 572 family caregivers of a person with Alzheimer's disease and related dementias (ADRD), our application of the J48 algorithm (C4.5) revealed an interesting trend. African American family members of a person with ADRD were more likely to see the benefits of using AI on social media to ease the burden of recruitment, regardless of age, ethnicity, gender, and level of education. However, white family caregivers, particularly those aged 25-34 with graduate degrees, were more cautious and prone to perceive risks of using AI on social media for recruitment in research. This caution underscores the need for further research and understanding in this area.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11984627 | PMC |
http://dx.doi.org/10.3233/SHTI250055 | DOI Listing |