{"id":142,"date":"2017-09-13T15:45:24","date_gmt":"2017-09-13T15:45:24","guid":{"rendered":"http:\/\/cps.engr.uga.edu\/?page_id=142"},"modified":"2017-09-13T17:35:57","modified_gmt":"2017-09-13T17:35:57","slug":"smart-secure-and-connected-healthcare-systems","status":"publish","type":"page","link":"https:\/\/cps.uga.edu\/index.php\/smart-secure-and-connected-healthcare-systems\/","title":{"rendered":"Smart, Secure and Connected Healthcare Systems"},"content":{"rendered":"<ul>\n<li>Medical and health sensors and medical robotics systems, human-robot interaction, computer-aided surgery<\/li>\n<li>Methods and algorithms for aggregation of multi-scale clinical, biomedical, contextual, and environmental data about each patient (e.g., in EHRs, personal health records &#8211; PHR, etc.), and unified and extensible metadata standards, and decision support tools to facilitate optimized patient-centered, evidence-based decisions.<\/li>\n<li>Underlying socioeconomic and behavioral principles underlying patient participation in healthcare and wellness.<\/li>\n<li>Parsing and mining the texts of the social media to accurately predict epidemics, such as flu; building statistical models to predict disease occurrence.<\/li>\n<li>Protocols and interface standards to enable interoperable, temporally synchronized, medical prosthetic and embedded devices and those devices for continuous capture, storage, and transmission of physiological state and environmental data.<\/li>\n<li>Interoperable, distributed, federated, secure and scalable digital infrastructure (such as Blockchain), languages, and tools for effective sharing and use of electronic health record data, data representation, and networked applications that access such data.<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-161 aligncenter\" src=\"http:\/\/cps.engr.uga.edu\/wp-content\/uploads\/2017\/09\/r2-300x86.png\" alt=\"\" width=\"767\" height=\"220\" srcset=\"https:\/\/cps.uga.edu\/wp-content\/uploads\/2017\/09\/r2-300x86.png 300w, https:\/\/cps.uga.edu\/wp-content\/uploads\/2017\/09\/r2.png 700w\" sizes=\"auto, (max-width: 767px) 100vw, 767px\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Medical and health sensors and medical robotics systems, human-robot interaction, computer-aided surgery Methods and algorithms for aggregation of multi-scale clinical, biomedical, contextual, and environmental data about each patient (e.g., in EHRs, personal health records &#8211; PHR, etc.), and unified and&hellip; <\/p>\n","protected":false},"author":1,"featured_media":161,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-142","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/pages\/142","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/comments?post=142"}],"version-history":[{"count":3,"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/pages\/142\/revisions"}],"predecessor-version":[{"id":176,"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/pages\/142\/revisions\/176"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/media\/161"}],"wp:attachment":[{"href":"https:\/\/cps.uga.edu\/index.php\/wp-json\/wp\/v2\/media?parent=142"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}