{"id":10558,"date":"2016-02-21T14:57:00","date_gmt":"2016-02-21T13:57:00","guid":{"rendered":"http:\/\/catai.net\/blog\/?p=10558"},"modified":"2019-09-20T13:23:14","modified_gmt":"2019-09-20T12:23:14","slug":"indivudualome-the-dashboard-of-health-small-data","status":"publish","type":"post","link":"https:\/\/catai.net\/blog\/2016\/02\/indivudualome-the-dashboard-of-health-small-data\/","title":{"rendered":"INDIVIDUALOME: The dashboard of health small data."},"content":{"rendered":"<p><strong><a href=\"http:\/\/bib.oxfordjournals.org\/content\/early\/2016\/02\/13\/bib.bbv118.full\">INDIVIDUALOMA MODEL<\/a><\/strong>&nbsp;have been defined. It captures temporal, categorical and continuous data elements about a patient from various biomedical, health care, wellness, social and environmental data streams. Initiatives to capture and integrate health, biomedical, multi-omic and clinical data, using a unified data model would help us to design precise, data-driven CDS and enable precision medicine as part of routine clinical practice in the near future.<\/p>\n<p>As published and stated in several posts, this is just the <a href=\"http:\/\/sco.lt\/7rnCFt\">dashboard of the personal Health Small Data<\/a> (pHSD) that belong to the individual patient or not,&nbsp;and that should be shared whenever necesary to either their PHAs (personal health assistants) or to the Medical personell with permission of the patient.<\/p>\n<p>Most of <a href=\"https:\/\/catai.net\/blog\/2015\/12\/data-analytics-in-healthcare\/\">this data should be capture and processed<\/a> in real time to detect risk factors that in many cases are build with joining multiple parameters and should be processed with Machine Learning tools to detect deviations of their homeostasis and normal pattern that each individual should have. The requirements of inmediate processing and respond require the presence in place of the <a href=\"https:\/\/catai.net\/blog\/2015\/12\/open-fog-and-hfog\/\">HealthFOG<\/a> (hFOG).<\/p>\n<p><a href=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma.jpg\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"225\" class=\"aligncenter size-medium wp-image-10560\" alt=\"Individualoma\" src=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-300x225.jpg\" srcset=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-300x225.jpg 300w, https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-600x450.jpg 600w, https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma.jpg 960w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/p>\n<p>Images from: &nbsp;<b>Khader<\/b> <b>Shameer<\/b><b> et al. Brief <\/b><b>Bioinform<\/b><b> 2016;bib.bbv118. &nbsp;http:\/\/bib.oxfordjournals.org\/content\/early\/2016\/02\/13\/b<\/b><b>ib.bbv118.full &nbsp;<\/b><\/p>\n<p>This dashboard could be enhanced using <a href=\"http:\/\/neo4j.com\/book-graph-databases\/?utm_source=GPPC&amp;gclid=CIrlhMGZicsCFQk8GwodmWgOmQ\">open source Graph data bases<\/a> that allow easy understanding of complex situations.<a href=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"460\" height=\"360\" class=\" wp-image-10562 alignright\" alt=\"Individualoma-2\" src=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-2-300x235.png\" srcset=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-2-300x235.png 300w, https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-2.png 599w\" sizes=\"auto, (max-width: 460px) 100vw, 460px\" \/><\/a><\/p>\n<p><a href=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-1.png\"><img loading=\"lazy\" decoding=\"async\" width=\"461\" height=\"424\" class=\" wp-image-10561 alignleft\" alt=\"Individualoma-1\" src=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-1-300x276.png\" srcset=\"https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-1-300x276.png 300w, https:\/\/catai.net\/blog\/wp-content\/uploads\/2016\/02\/Individualoma-1.png 600w\" sizes=\"auto, (max-width: 461px) 100vw, 461px\" \/><\/a><\/p>\n<p><script src=\"https:\/\/apis.google.com\/_\/scs\/apps-static\/_\/js\/k=oz.gapi.es.W4rlJ_oaRVQ.O\/m=auth\/exm=plusone\/rt=j\/sv=1\/d=1\/ed=1\/am=EQ\/rs=AGLTcCMIj0dX30VXPxvsSkwfBZb0nIuhig\/t=zcms\/cb=gapi.loaded_1\" async=\"\"><\/script><\/p>\n<p><iframe loading=\"lazy\" width=\"300\" height=\"150\" src=\"http:\/\/players.brightcove.net\/1824526989001\/default_default\/index.html?videoId=4764781062001\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>INDIVIDUALOMA MODEL&nbsp;have been defined. It captures temporal, categorical and continuous data elements about a patient from various biomedical, health care, wellness, social and environmental data streams. Initiatives to capture and integrate health, biomedical, multi-omic and clinical data, using a unified data model would help us to design precise, data-driven CDS and enable precision medicine as [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":12456,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"give_campaign_id":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[43,35,22,3,40,13,24,26,66,28,29,32,9],"tags":[],"class_list":["post-10558","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-health-4-0","category-idi","category-inclusion","category-informes","category-innovacion","category-phealth","category-productividad","category-publicaciones","category-reverse-innovation","category-sanidad","category-seguridad","category-sociedad_red","category-unesco"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>INDIVIDUALOME: The dashboard of health small data. | Telemedicina<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/catai.net\/blog\/2016\/02\/indivudualome-the-dashboard-of-health-small-data\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"INDIVIDUALOME: The dashboard of health small data. | Telemedicina\" \/>\n<meta property=\"og:description\" content=\"INDIVIDUALOMA MODEL&nbsp;have been defined. It captures temporal, categorical and continuous data elements about a patient from various biomedical, health care, wellness, social and environmental data streams. 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