Programming Tools for Messenger-Based Chatbot System Organization: Implication for Outpatient and Translational Medicines

The implementation of translational medicine is associated with considerable costs of equipment, staff competence, and doctor-patient (DP) and clinic-patient (CP) communication. The application of DP and CP systems evolved from e-mail letters to website assistance chat and smartphone apps in the con...

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Published in:	BioNanoScience Vol. 7; no. 2; pp. 403 - 407
Main Authors:	Abashev, Almir, Grigoryev, Ruslan, Grigorian, Karen, Boyko, Vladislav
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2017 Springer Nature B.V
Subjects:	Applications programs Biological and Medical Physics Biomaterials Biophysics Chatbots Circuits and Systems Communication Communications equipment Conversation Electronic devices Engineering Equipment costs Human communication Integration Mail Medicine Mobile computing Nanotechnology Personal communication Translation Chatbot Ambulatory medicine Outpatient medicine Artificial intelligence Translational medicine Communication
ISSN:	2191-1630, 2191-1649
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Abstract	The implementation of translational medicine is associated with considerable costs of equipment, staff competence, and doctor-patient (DP) and clinic-patient (CP) communication. The application of DP and CP systems evolved from e-mail letters to website assistance chat and smartphone apps in the context of the m-health paradigm. The rapid development of mobile messengers and chatbot systems has opened a new niche for DP and CP communication, providing a high population penetration rate with perfect capabilities for personalization. This article provides a model of chatbot system organization as well as programming tools for its implementation. The integration of machine conversation systems supplemented by natural spoken language together with m-health devices and mobile apps is a good solution for a variety of tasks in translational and outpatient medicine. The usage of chatbot systems as a communication device for the purposes of translational medicine is going to reduce costs and time on routine operations.
AbstractList	The implementation of translational medicine is associated with considerable costs of equipment, staff competence, and doctor-patient (DP) and clinic-patient (CP) communication. The application of DP and CP systems evolved from e-mail letters to website assistance chat and smartphone apps in the context of the m-health paradigm. The rapid development of mobile messengers and chatbot systems has opened a new niche for DP and CP communication, providing a high population penetration rate with perfect capabilities for personalization. This article provides a model of chatbot system organization as well as programming tools for its implementation. The integration of machine conversation systems supplemented by natural spoken language together with m-health devices and mobile apps is a good solution for a variety of tasks in translational and outpatient medicine. The usage of chatbot systems as a communication device for the purposes of translational medicine is going to reduce costs and time on routine operations.
Author	Abashev, Almir Grigoryev, Ruslan Grigorian, Karen Boyko, Vladislav
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AR Spielberg (376_CR7) 1998; 280 BA Shawar (376_CR19) 2005; 10 B Gaster (376_CR5) 2003; 18 376_CR31 376_CR32 376_CR30 376_CR13 376_CR35 AM Turing (376_CR20) 1950; 59 376_CR33 376_CR12 VL Rubin (376_CR25) 2010; 28 376_CR34 376_CR28 376_CR29 J Ye (376_CR6) 2010; 80 SS Gollamudi (376_CR14) 2016; 4 NS Baron (376_CR17) 2004; 23 AZ Fan (376_CR36) 2013; 5 WJ Wilbur (376_CR39) 1992; 18 R Crutzen (376_CR27) 2011; 48 D-Y Hu (376_CR8) 2016 M Swan (376_CR9) 2009; 6 376_CR1 376_CR21 376_CR3 376_CR40 376_CR2 376_CR24 X Xu (376_CR11) 2015; 103 376_CR23 376_CR18 376_CR37 376_CR16 376_CR38 KK Marciel (376_CR26) 2010; 45 A Andal-Ancion (376_CR4) 2003; 44 JL Hutchens (376_CR22) 1996 A Bastawrous (376_CR10) 2013; 106 SA Tagliamonte (376_CR15) 2008; 83
References_xml	– reference: Java Telegram bot API documentation. https://github.com/rubenlagus/TelegramBots – reference: Walton, N. (2014). Chat apps will disrupt global telecoms sector. The Oxford Analytica Daily Brief. – reference: YeJRustGFry-JohnsonYStrothersHE-mail in patient-provider communication: a systematic reviewPatient Educ Couns201080226627310.1016/j.pec.2009.09.038 – reference: BastawrousAArmstrongMJMobile health use in low-and high-income countries: an overview of the peer-reviewed literatureJ R Soc Med2013106413014210.1177/0141076812472620 – reference: TagliamonteSADenisDLinguistic ruin? LOL! Instant messaging and teen languageAmerican speech200883133410.1215/00031283-2008-001 – reference: Andal-AncionACartwrightPYipGSThe digital transformation of traditional businessMIT Sloan Manag Rev20034443441 – reference: Bates, M., & Zumla, A. (2015). Rapid infectious diseases diagnostics using smartphones. Annals of translational medicine, 3(15). doi:10.3978/j.issn.2305-5839.2015.07.07. – reference: Edoja, D. (2011). Method, system and program for data delivering using chatbot: Google Patents. – reference: Carrara, S., Baj-Rossi, C., Ghoreishizadeh, S. S., Riario, S., Surrel, G., Stradolini, F., … Dehollain, C. (2015). Full system for translational studies of personalized medicine with free-moving mice. In Paper presented at the 2015 I.E. International Symposium on Circuits and Systems (ISCAS). – reference: Fiebach, N. H., Barker, L. R., Burton, J. R., & Zieve, P. D. (2007). Principles of ambulatory medicine. Lippincott Williams & Wilkins. – reference: WilburWJSirotkinKThe automatic identification of stop wordsJ Inf Sci1992181455510.1177/016555159201800106 – reference: HutchensJLHow to pass the Turing test by cheating. School of Electrical, electronic and computer engineering research report TR97–051996PerthUniversity of Western Australia – reference: BaronNSSee you online gender issues in college student use of instant messagingJ Lang Soc Psychol2004234397423203478810.1177/0261927X04269585 – reference: FanAZLiYElam-EvansLDBalluzLDrinking pattern and blood pressure among non-hypertensive current drinkers: findings from 1999 to 2004 National Health and Nutrition Examination SurveyClin Epidemiol20135212710.2147/CLEP.S12152 – reference: SwanMEmerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-trackingInt J Environ Res Public Health20096249252510.3390/ijerph6020492 – reference: Akka Java documentation. http://akka.io/docs/ – reference: Mikolov, T., Chen, K., Corrado, G., Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781. – reference: MarcielKKSaimanLQuittellLMDawkinsKQuittnerALCell phone intervention to improve adherence: cystic fibrosis care team, patient, and parent perspectivesPediatr Pulmonol201045215716410.1002/ppul.21164 – reference: Segalovich, I. (2003). A fast morphological algorithm with unknown word guessing induced by a dictionary for a web search engine. In Paper presented at the MLMTA. – reference: HuD-YMass prevention and treatment: fundamental strategy for chronic disease control and preventionChronic Diseases and Translational Medicine2016 – reference: TuringAMComputing machinery and intelligenceMind1950592364334603706410.1093/mind/LIX.236.433 – reference: CrutzenRPetersG-JYPortugalSDFisserEMGrollemanJJAn artificially intelligent chat agent that answers adolescents’ questions related to sex, drugs, and alcohol: an exploratory studyJ Adolesc Health201148551451910.1016/j.jadohealth.2010.09.002 – reference: SpielbergAROn call and online: sociohistorical, legal, and ethical implications of e-mail for the patient-physician relationshipJAMA1998280151353135910.1001/jama.280.15.1353 – reference: MyStem documentation. https://tech.yandex.ru/mystem/ – reference: Westerman, G., Bonnet, D., & McAfee, A. (2014). The nine elements of digital transformation. MIT Sloan Manag Rev, 7. – reference: Abraham, A. (2005). Rule-Based expert systems. Handbook of measuring system design. – reference: ShawarBAAtwellESUsing corpora in machine-learning chatbot systemsInternational journal of corpus linguistics200510448951610.1075/ijcl.10.4.06sha – reference: Agostaro, F., Augello, A., Pilato, G., Vassallo, G., Gaglio, S. (2005). A conversational agent based on a conceptual interpretation of a data driven semantic space. In Paper presented at the Congress of the Italian Association for Artificial Intelligence. – reference: Ghose, S., Barua, J. J. (2013). Toward the implementation of a topic specific dialogue based natural language chatbot as an undergraduate advisor. In Paper presented at the Informatics, Electronics & Vision (ICIEV), 2013 International Conference on. – reference: ElasticSearch Java API documentation. https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/index.html – reference: RubinVLChenYThorimbertLMArtificially intelligent conversational agents in librariesLibrary Hi Tech201028449652210.1108/07378831011096196 – reference: Person, N., Graesser, A. C., Group, T. R. (2002). Human or computer? Autotutor in a bystander turing test. In Paper presented at the International Conference on Intelligent Tutoring Systems. – reference: Kuhn, R., Hanafee, B., Allen, J. (2014). Reactive design patterns: Manning publications. – reference: Schiano, D. J., Chen, C. P., Isaacs, E., Ginsberg, J., Gretarsdottir, U., Huddleston, M. (2002). Teen use of messaging media. In Paper presented at the CHI’02 extended abstracts on Human factors in computing systems. – reference: Shawar, B. A., Atwell, E. (2002). A comparison between ALICE and Elizabeth chatbot systems. – reference: GasterBKnightCLWittDESheffieldJVAssefiNPBuchwaldDPhysicians’ use of and attitudes toward electronic mail for patient communicationJ Gen Intern Med200318538538910.1046/j.1525-1497.2003.20627.x – reference: GollamudiSSTopolEJWineingerNEA framework for smartphone-enabled, patient-generated health data analysisPeerJ Preprints20164e1911v1911 – reference: Batacharia, B., Levy, D., Catizone, R., Krotov, A., Wilks, Y. (1999). CONVERSE: a conversational companion Machine conversations (pp. 205–215). Springer. – reference: Montano, M. (2014). Translational biology in medicine. 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SubjectTerms	Applications programs Biological and Medical Physics Biomaterials Biophysics Chatbots Circuits and Systems Communication Communications equipment Conversation Electronic devices Engineering Equipment costs Human communication Integration Mail Medicine Mobile computing Nanotechnology Personal communication Translation
Title	Programming Tools for Messenger-Based Chatbot System Organization: Implication for Outpatient and Translational Medicines
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