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
Global aging population, especially with the global pandemic outbreak of the Corona Virus Disease 2019 (COVID-19), has endangered human health security. Digital information technology through big data empowerment and intelligent application is widely considered a key element to solve the problems. Stroke is a life-threaten disorder. We studied individual health management and disease risk perception using human health assessment model and make full use of wearable wireless sensor, Internet of Things, big data, and Artificial Intelligence for potential risk monitoring and real-time stroke warning. We proposed an effective method of monitoring, early warning and rescue to improve the stroke treatment. The result shows that the health management empowered by big data can generate new opportunities and ideas to solve early detection and warning of stroke.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871473 | PMC |
http://dx.doi.org/10.1016/j.compeleceng.2023.108602 | DOI Listing |
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