{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:31:48Z","timestamp":1777703508465,"version":"3.51.4"},"reference-count":62,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2016,12,23]],"date-time":"2016-12-23T00:00:00Z","timestamp":1482451200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2017,1,30]]},"abstract":"<jats:p>Healthcare is one of the most important concerns of society, being extremely relevant the accuracy and quality of their services. Basically, eHealth can be considered as the area where electronic processes and communications are used to improve the quality of medical assistance. Despite the relative maturity of the field, recalls and problems related to medical devices, applications and services are still very frequent. Therefore, it is necessary to improve and expand current research to provide advances that can be transmitted to the society. As an initial step, it is essential to have a good understanding of the current state-of-the-art of eHealth. The main goal of this paper is to identify the most relevant and recent work on eHealth but, due to the immensity of the field and the scope of the journal, we will concentrate on the use of two specific technologies: databases and collective intelligence. In addition to review the main concepts related to eHealth and the most influent academic papers, we will describe projects which are essential for the correct performance of many healthcare services. As a result of our study, we reached some interesting conclusions that might be useful for future projects and we encourage to apply them in order to avoid some of the problems that we have found in existing projects.<\/jats:p>","DOI":"10.3233\/jifs-169144","type":"journal-article","created":{"date-parts":[[2016,12,23]],"date-time":"2016-12-23T17:51:38Z","timestamp":1482515498000},"page":"1485-1496","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Collective intelligence and databases in\u00a0eHealth: A survey"],"prefix":"10.1177","volume":"32","author":[{"given":"Azahara","family":"Camacho","sequence":"first","affiliation":[{"name":"Departamento de Sistemas Inform\u00e1ticos y Computaci\u00f3n, Facultad de Inform\u00e1tica, Universidad Complutense de Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mercedes G.","family":"Merayo","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas Inform\u00e1ticos y Computaci\u00f3n, Facultad de Inform\u00e1tica, Universidad Complutense de Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuel","family":"N\u00fa\u00f1ez","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas Inform\u00e1ticos y Computaci\u00f3n, Facultad de Inform\u00e1tica, Universidad Complutense de Madrid, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,12,23]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"690","article-title":"Toward collective intelligence for fighting obesity","author":"Addo I.","year":"2013","unstructured":"AddoI., AhamedS. and ChuW., Toward collective intelligence for fighting obesity. 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