96080 20210902121610.0 doi 10.1016/j.jbi.2019.103305 sideral 115725 ART-2020-115725 eng (orcid)0000-0003-2608-6431 Roca, Surya Universidad de Zaragoza Microservice chatbot architecture for chronic patient support 2020 Access copy available to the general public Unrestricted Chatbots are able to provide support to patients suffering from very different conditions. Patients with chronic diseases or comorbidities could benefit the most from chatbots which can keep track of their condition, provide specific information, encourage adherence to medication, etc. To perform these functions, chatbots need a suitable underlying software architecture. In this paper, we introduce a chatbot architecture for chronic patient support grounded on three pillars: scalability by means of microservices, standard data sharing models through HL7 FHIR and standard conversation modeling using AIML. We also propose an innovative automation mechanism to convert FHIR resources into AIML files, thus facilitating the interaction and data gathering of medical and personal information that ends up in patient health records. To align the way people interact with each other using messaging platforms with the chatbot architecture, we propose these very same channels for the chatbot-patient interaction, paying special attention to security and privacy issues. Finally, we present a monitored-data study performed in different chronic diseases, and we present a prototype implementation tailored for one specific chronic disease, psoriasis, showing how this new architecture allows the change, the addition or the improvement of different parts of the chatbot in a dynamic and flexible way, providing a substantial improvement in the development of chatbots used as virtual assistants for chronic patients. info:eu-repo/grantAgreement/ES/DGA/T31-17R info:eu-repo/grantAgreement/ES/MINECO/BES-2017-082017 info:eu-repo/grantAgreement/ES/MINECO/TIN2016-76770-R info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 6.317 2020 MEDICAL INFORMATICS 3 / 30 = 0.1 2020 Q1 T1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 13 / 112 = 0.116 2020 Q1 T1 1.056 2020 Health Informatics 2020 Q1 Computer Science Applications 2020 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion (orcid)0000-0001-8518-6884 Sancho, Jorge Universidad de Zaragoza (orcid)0000-0001-9485-7678 García, José Universidad de Zaragoza (orcid)0000-0002-5254-1402 Alesanco, Álvaro Universidad de Zaragoza 5008 560 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Ingeniería Telemática 102 (2020), 103305 1-9 J. Biomed. Inform Journal of Biomedical Informatics 1532-0464 10366696 http://zaguan.unizar.es/record/96080/files/texto_completo.pdf Postprint 232445 http://zaguan.unizar.es/record/96080/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:96080 articulos driver 2021-09-02-08:40:46 ARTICLE