Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective

El objetivo principal de esta tesis es analizar y evaluar la complejidad de la cultura de la empresa que debido a los nuevos entornos empresariales y las nuevas dinámicas internas de trabajo ha cambiado de diversas formas. Esta tesis examina el papel de la inteligencia artificial en las organizacion...

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Fecha de publicación:: 2019

Institución:: Universidad del Rosario

Repositorio:: Repositorio EdocUR - U. Rosario

Idioma:: eng

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dc.title.eng.fl_str_mv	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
dc.title.alternative.spa.fl_str_mv	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
title	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
spellingShingle	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective Inteligencia Artificial Aprendizaje automatizado Redes neuronales Industria Farmacéutica Investigación y Desarrollo Innovación Tendencias del Futuro Sistemas Inteligentes Artificial Intelligence Machine Learning Neural Networks Pharmaceutical Industry R&D Innovation Future Trends Drug discovery Intelligent systems Firm outcomes
title_short	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
title_full	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
title_fullStr	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
title_full_unstemmed	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
title_sort	Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective
dc.contributor.advisor.none.fl_str_mv	Mazloomi Khamseh, Hamid
dc.subject.spa.fl_str_mv	Inteligencia Artificial Aprendizaje automatizado Redes neuronales Industria Farmacéutica Investigación y Desarrollo Innovación Tendencias del Futuro Sistemas Inteligentes
topic	Inteligencia Artificial Aprendizaje automatizado Redes neuronales Industria Farmacéutica Investigación y Desarrollo Innovación Tendencias del Futuro Sistemas Inteligentes Artificial Intelligence Machine Learning Neural Networks Pharmaceutical Industry R&D Innovation Future Trends Drug discovery Intelligent systems Firm outcomes
dc.subject.keyword.spa.fl_str_mv	Artificial Intelligence
dc.subject.keyword.eng.fl_str_mv	Machine Learning Neural Networks Pharmaceutical Industry R&D Innovation Future Trends Drug discovery Intelligent systems Firm outcomes
description	El objetivo principal de esta tesis es analizar y evaluar la complejidad de la cultura de la empresa que debido a los nuevos entornos empresariales y las nuevas dinámicas internas de trabajo ha cambiado de diversas formas. Esta tesis examina el papel de la inteligencia artificial en las organizaciones y la forma en que influye en la innovación y la I + D. Además, este proyecto evalúa y analiza los retos a los que se enfrentan las empresas para optimizar sus recursos, incrementar la innovación, incorporar la I + D en función del tamaño, la cultura corporativa y el presupuesto disponible que debido a los nuevos entornos de negocio y las nuevas dinámicas internas de trabajo ha tenido que cambiar considerablemente. Además, analiza la tendencia de los nuevos usos de las redes neuronales artificiales para analizar datos y como nueva herramienta para desarrollar en profundidad la IA en las empresas. En esta investigación, voy a seleccionar la Industria Farmacéutica, para analizarla. Además, esta visión identificará la relación proporcional de los instrumentos de IA y los crecientes resultados. Por otro lado, este estudio quiere proponer una nueva forma de cómo la IA puede cambiar las organizaciones en un contexto corporativo, mediante el uso de la innovación y su aplicación en todo el proceso de I + D. Sabiendo esto, el enfoque propuesto quiere comprender los componentes más importantes de la toma de decisiones de la empresa utilizando nuevas tecnologías, como la IA.
publishDate	2019
dc.date.created.none.fl_str_mv	2019-10-28
dc.date.accessioned.none.fl_str_mv	2021-02-16T17:55:06Z
dc.date.available.none.fl_str_mv	2021-02-16T17:55:06Z
dc.type.eng.fl_str_mv	bachelorThesis
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dc.type.document.spa.fl_str_mv	Trabajo de grado
dc.type.spa.spa.fl_str_mv	Trabajo de grado
dc.identifier.doi.none.fl_str_mv	https://doi.org/10.48713/10336_30917
dc.identifier.uri.none.fl_str_mv	https://repository.urosario.edu.co/handle/10336/30917
url	https://doi.org/10.48713/10336_30917 https://repository.urosario.edu.co/handle/10336/30917
dc.language.iso.none.fl_str_mv	eng
language	eng
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rights_invalid_str_mv	Atribución-NoComercial-SinDerivadas 2.5 Colombia Abierto (Texto Completo) http://creativecommons.org/licenses/by-nc-nd/2.5/co/ http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv	application/pdf
dc.publisher.none.fl_str_mv	Universidad del Rosario
dc.publisher.department.none.fl_str_mv	Escuela de Administración
dc.publisher.program.none.fl_str_mv	Administración de Negocios Internacionales
publisher.none.fl_str_mv	Universidad del Rosario
institution	Universidad del Rosario
dc.source.bibliographicCitation.none.fl_str_mv	Romeo, L., Loncarski, J., Paolanti, M., Bocchini, G., Mancini, A., & Frontoni, E. (2020). Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0. Expert Systems With Applications, 140. https://doi-org.ez.urosario.edu.co/10.1016/j.eswa.2019.112869 Fast, N. J., & Schroeder, J. (2020). Power and decision making: new directions for research in the age of artificial intelligence. Current opinion in psychology, 33, 172–176. https://doi.org/10.1016/j.copsyc.2019.07.039 Campus, A. (2019). Corporate Financial Evaluation and Bankruptcy Prediction Implementing Artificial Intelligence Methods. Retrieved from: http://www.wseas.us/e-library/conferences/2006cscc/papers/534-877.pdf [Accessed 26 Sept. 2019]. Griliches, Z. (1984). R&D and Innovation: Some Empirical Findings. Retrieved from: https://www.nber.org/chapters/c10047.pdf Hameed, Farhan, Iqbal, W. (2018). Determinants of Firm’s open innovation performance and the role of R & D department: an empirical evidence from Malaysian SME’s. Retrieved from: https://journal-jger.springeropen.com/track/pdf/10.1186/s40497-018-0112-8 Xiuqin Li, Dimitri Gagliardi & Ian Miles (2019) Innovation in R&D service firms: evidence from the UK, Technology Analysis & Strategic Management, 31:6, 732-748, DOI: 10.1080/09537325.2018.1549729 Siraj, Hussain, F. (2008). ARTIFICIAL INTELLIGENCE IN MEDICAL APPLICATION: AN EXPLORATION. Retrieved from: https://www.researchgate.net/profile/Wan_Hussain_Wan_Ishak/publication/240943548_ARTIFICIAL_INTELLIGENCE_IN_MEDICAL_APPLICATION_AN_EXPLORATION/links/00b7d5292d45d674ab000000.pdf Tull, E. Miller, S. (2019). The Journal of Robotics, Artificial Intelligence & Law. Retrieved from: https://www.finnegan.com/images/content/1/9/v2/197825/PUBLISHED-The-Journal-of-Robotics-Artificial-Intelligence-L.pdf Li, Gagliardi, Miles, X. (2018). Innovation in R&D service firms: evidence from the UK. Retrieved from: https://www-tandfonline-com.ez.urosario.edu.co/doi/full/10.1080/09537325.2018.1549729 Ramesh, Kambhampati, Monson, A. (2004). Artificial intelligence in medicine. Retrieved from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1964229/pdf/15333167.pdf Katherine Wolf, Nakia Woodward & Richard Wallace (2013) ClinicalKey: A Review, Journal of Electronic Resources in Medical Libraries, 10:2, 79-87, DOI: 10.1080/15424065.2013.792592 Alexander, A., McGill, M., Tarasova, A., Ferreira, C. and Zurkiya, D. (2019). Scanning the Future of Medical Imaging. Retrieved from: https://www-clinicalkey-es.ez.urosario.edu.co/#!/content/playContent/1-s2.0S1546144018312821?returnurl=null&referrer=null Hengstler, M., Enkel, E. and Duelli, S. (2016). Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices. Retrieved from: https://www-sciencedirect-com.ez.urosario.edu.co/science/article/pii/S0040162515004187 Impedovo, D. and Pirlo, G. (2019). eHealth and Artificial Intelligence. Retrieved from: http://file:///C:/Users/anama/Downloads/eHealth-and-artificial-intelligence2019Information-SwitzerlandOpen-Access.pdf Tsang, L., Kracov, D., Mulryne, J., Strom, L., Perkins, N., Dickinson, R., Wallace, V. and Jones, B. (2019). The Impact of Artificial Intelligence on Medical Innovation in the European Union and United States. Retrieved from: https://www.arnoldporter.com/-/media/files/perspectives/publications/2017/08/the-impact-of-artificial-inteelligence-on-medical-innovation.pdf Mateos-Garcia, J. (2018). The Complex Economics of Artificial Intelligence. Retrieved from: https://www.nesta.org.uk/blog/complex-economics-artificial-intelligence/ Fast, N. and Schroeder, J. (2019). Power and decision making: new directions for research in the age of artificial intelligence. Retrieved from: http://file:///C:/Users/anama/Downloads/Power-and-decision-making-new-directions-for-research-in-the-age-of-artificial-intelligence2020Current-Opinion-in-Psychology.pdf. Nogueira, R., Pini, F., Otávio, M. and Lúcia Chicarelli, R. (2014). Analyzing effects of external integration on innovations outcomes in large and non-large Brazilian food companies. Retrieved from: https://www.researchgate.net/publication/263287843_Analyzing_effects_of_external_integration_on_innovations_outcomes_in_large_and_non-large_Brazilian_food_companies Levy, S. (2018) ‘Intelligent Business: Pharmacy software companies look to enable better outcomes, clinical interventions’, Drug Store News, 40(11), p. 38. Retrieved from: http://search.ebscohost.com.ez.urosario.edu.co/login.aspx?direct=true&db=f5h&AN=132843977&lang=es&site=eds-live&scope=site. Jespersen, K. R. (2018). Crowdsourcing design decisions for optimal integration into the company innovation system. Decision Support Systems, 115, 52–63. https://doi-org.ez.urosario.edu.co/10.1016/j.dss.2018.09.005 Hengstler, M., Enkel, E. and Duelli, S. (2019). Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices. Retrieved from: https://www-sciencedirect-com.ez.urosario.edu.co/science/article/pii/S0040162515004187 Tsang, L., Kracov, D., Mulryne, J., Strom, L., Perkins, N., Dickinson, R., Wallace, V. and Jones, B. (2019). The Impact of Artificial Intelligence on Medical Innovation in the European Union and United States. Retrieved from: https://www.arnoldporter.com/~/media/files/perspectives/publications/2017/08/the-impact-of-artificial-inteelligence-on-medical-innovation.pdf Lichtenthaler, U. (2020), "Beyond artificial intelligence: why companies need to go the extra step", Journal of Business Strategy, Vol. 41 No. 1, pp. 19-26. https://doi.org/10.1108/JBS-05-2018-0086 Jean Paul Simon, author (2019) ‘Artificial intelligence: scope, players, markets and geography’, Digital Policy, Regulation and Governance, (3), p. 208. doi: 10.1108/DPRG-08-2018-0039. Agrawal, A., Gans, J. and Goldfarb, A. (2019). What to Expect From Artificial Intelligence. Retrieved from: https://sloanreview.mit.edu/article/what-to-expect-from-artificial-intelligence/ Yamakawa, P. and Ostos, J. (2011). Relación entre innovación organizacional y desempeño organizacional. Retrieved from: https://revistas.urosario.edu.co/index.php/empresa/article/view/1889 Amato, F. et al. (no date) ‘Chatbots meet ehealth: Automatizing healthcare’, CEUR Workshop Proceedings, 1982, pp. 40–49. Retrieved from: http://search.ebscohost.com.ez.urosario.edu.co/login.aspx?direct=true&db=edselc&AN=edselc.2-52.0-85034835878&lang=es&site=eds-live&scope=site Mansury, M. A., & Love, J. H. (2008). Innovation, productivity and growth in US business services: A firm-level analysis. Technovation, 28(1), 52–62. https://doi-org.ez.urosario.edu.co/10.1016/j.technovation.2007.06.002 Klinger, J., Mateos-Garcia, J. and Stathoulopoulos, K. (2018). Deep Learning, Deep Change? Mapping the Development of the Artificial Intelligence General Purpose Technology. SSRN Electronic Journal. Mateos-García, J. (2018). The Complex Economics of Artificial Intelligence. Nesta. Retrieved from: https://www.nesta.org.uk/blog/complex-economics-artificial-intelligence/ Kazuyuki, M. (2018). Understanding AI Driven Innovation by Linked Database of Scientific Articles and Patents. RIETI Policy Discussion Paper Series 18-P-017. Retrieved from: https://www.rieti.go.jp/jp/publications/pdp/18p017.pdf Guellec, D., Paunov, C., (2018). Innovation Policies in the Digital Age. OECD publishing No.59. Retrieved from: http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DSTI/STP/TIP(2018)5/FINAL&docLanguage=En Shahid, N., Rappon, T., & Berta, W. (2019). Applications of artificial neural networks in health care organizational decision-making: A scoping review. PLoS ONE, 14(2), 1–22. https://doi-org.ez.urosario.edu.co/10.1371/journal.pone.0212356 Moshe A. Barach, Aseem Kaul, Ming D. Leung, & Sibo Lu. (2019). Strategic Redundancy in the Use of Big Data: Evidence from a Two-Sided Labor Market. Strategy Science, 4, 298. https://doi-org.ez.urosario.edu.co/10.1287/stsc.2019.0093. Ting, K., Lee, R., Milne, G., Shapiro, M. and Guarino, A. (1973). Applications of Artificial Intelligence: Relationships between Mass Spectra and Pharmacological Activity of Drugs. Science, 180(4084), pp.417-420. Namaki, M. S. S. E. (2018). How Companies are Applying AI to the Business Strategy Formulation. Scholedge International Journal of Business Policy & Governance, 5(8), 77–82. https://doi-org.ez.urosario.edu.co/10.19085/journal.sijbpg050801 Study Data from University of Vaasa Provide New Insights into Industrial Change (Internationalization of corporate R&D activities and innovation performance). (2017, March 4). Investment Weekly News, 792. Nadia Ayari. (2010). Internal Capabilities, R&D Cooperation with Universities and Firms Innovativeness Level: Evidence from Spain. Faculty Working Papers. Cockburn, Iain.., Henderson, Rebecca., Stern, Scott. (2017). The impact of Artificial Intelligence on Innovation. Retrieved from: https://www.nber.org/chapters/c14006.pdf Ray, Tiernan. (2019). Finding New Cures in Old Drugs. ISSN: 0015-8259. Retrieved From: Fortune. 4/1/2019, Vol. 179 Issue 4, p74-79. 6p. 2 Color Photographs, 1 Diagram. Lichtenthaler, U. (2018). The world’s most innovative companies: a meta-ranking \| Emerald Insight. [online] Emerald.com. Retrieved from: https://www.emerald.com/insight/content/doi/10.1108/JSMA-07-2018-0065/full/html Song, J. and Zhang, Z. (2019). A Modified Robust FCM Model with Spatial Constraints for Brain MR Image Segmentation. Retrieved from: https://www.mdpi.com/2078-2489/10/2/74/pdf Demirdogen, G., & Isik, Z. (2016). Effect of internal capabilities on success of construction company innovation and technology transfer/Ucinak vlastitog potencijala na uspjesnost inovacija i prijenosa tehnologije u gradevinskom poduzecu. Tehnicki Vjesnik - Technical Gazette, 6, 1763. https://doi-org.ez.urosario.edu.co/10.17559/TV-20151222154916 Hsu, C.-L., Tseng, K. C., & Chuang, Y.-H. (2012). A secure IRB system for assisting the development of intelligent medical devices. Expert Systems With Applications, 39(16), 12512–12521. https://doi-org.ez.urosario.edu.co/10.1016/j.eswa.2012.04.062 Gilvary, C., Madhukar, N., Elkhader, J., & Elemento, O. (2019). The Missing Pieces of Artificial Intelligence in Medicine. Trends in Pharmacological Sciences, 40(8), 555–564. https://doi-org.ez.urosario.edu.co/10.1016/j.tips.2019.06.001 Hsu, C.-L., Tseng, K. C., & Chuang, Y.-H. (2012). A secure IRB system for assisting the development of intelligent medical devices. Expert Systems With Applications, 39(16), 12512–12521. https://doi-org.ez.urosario.edu.co/10.1016/j.eswa.2012.04.062
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spelling	Mazloomi Khamseh, Hamidd23ead90-700f-4c5f-a524-57a2b6ce975c600Arciniegas Jiménez, Ana MaríaAdministrador de Negocios InternacionalesFull time5baea803-0c7c-4ca4-a773-072470f198326002021-02-16T17:55:06Z2021-02-16T17:55:06Z2019-10-28El objetivo principal de esta tesis es analizar y evaluar la complejidad de la cultura de la empresa que debido a los nuevos entornos empresariales y las nuevas dinámicas internas de trabajo ha cambiado de diversas formas. Esta tesis examina el papel de la inteligencia artificial en las organizaciones y la forma en que influye en la innovación y la I + D. Además, este proyecto evalúa y analiza los retos a los que se enfrentan las empresas para optimizar sus recursos, incrementar la innovación, incorporar la I + D en función del tamaño, la cultura corporativa y el presupuesto disponible que debido a los nuevos entornos de negocio y las nuevas dinámicas internas de trabajo ha tenido que cambiar considerablemente. Además, analiza la tendencia de los nuevos usos de las redes neuronales artificiales para analizar datos y como nueva herramienta para desarrollar en profundidad la IA en las empresas. En esta investigación, voy a seleccionar la Industria Farmacéutica, para analizarla. Además, esta visión identificará la relación proporcional de los instrumentos de IA y los crecientes resultados. Por otro lado, este estudio quiere proponer una nueva forma de cómo la IA puede cambiar las organizaciones en un contexto corporativo, mediante el uso de la innovación y su aplicación en todo el proceso de I + D. Sabiendo esto, el enfoque propuesto quiere comprender los componentes más importantes de la toma de decisiones de la empresa utilizando nuevas tecnologías, como la IA.The main purpose of this thesis is to analyze and evaluate the company culture complexity which due to the new business environments and the new internal work dynamics has changed in several ways. This thesis examines the role of Artificial Intelligence in the organizations and the way it influences innovation and R&D. Moreover, this project evaluates and analyze the challenges, which the companies are facing to optimize their resources, increment innovation, incorporate R&D depending on the size, corporate culture and available budget that due to the new business environments and the new internal dynamics to work has changed considerably. Furthermore, it analyzes the tendency of the new uses of artificial neural networks to analyze data and as a new tool to develop in-depth the AI in the companies. In this research, I am going to select a specific industry to be analyzed, the Pharmaceutical Industry. This paper will reach all the processes from the R&D and innovation area of the companies that AI affect. In addition, this vision will identify the proportional relation of AI instruments and the increasing outcomes. On the other hand, this study wants to purpose a new way of how AI can change organizations in a corporate context, through the usage of innovation and the application of it in the whole process of R&D. Knowing this, the proposed approach wants to understand the most important components of company decision making using new technologies, such as AI.application/pdfhttps://doi.org/10.48713/10336_30917https://repository.urosario.edu.co/handle/10336/30917engUniversidad del RosarioEscuela de AdministraciónAdministración de Negocios InternacionalesAtribución-NoComercial-SinDerivadas 2.5 ColombiaAbierto (Texto Completo)EL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma. PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe. EL AUTOR, autoriza a LA UNIVERSIDAD DEL ROSARIO, para que en los términos establecidos en la Ley 23 de 1982, Ley 44 de 1993, Decisión andina 351 de 1993, Decreto 460 de 1995 y demás normas generales sobre la materia, utilice y use la obra objeto de la presente autorización. -------------------------------------- POLITICA DE TRATAMIENTO DE DATOS PERSONALES. Declaro que autorizo previa y de forma informada el tratamiento de mis datos personales por parte de LA UNIVERSIDAD DEL ROSARIO para fines académicos y en aplicación de convenios con terceros o servicios conexos con actividades propias de la academia, con estricto cumplimiento de los principios de ley. Para el correcto ejercicio de mi derecho de habeas data cuento con la cuenta de correo habeasdata@urosario.edu.co, donde previa identificación podré solicitar la consulta, corrección y supresión de mis datos.http://creativecommons.org/licenses/by-nc-nd/2.5/co/http://purl.org/coar/access_right/c_abf2Romeo, L., Loncarski, J., Paolanti, M., Bocchini, G., Mancini, A., & Frontoni, E. (2020). Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0. Expert Systems With Applications, 140. https://doi-org.ez.urosario.edu.co/10.1016/j.eswa.2019.112869Fast, N. J., & Schroeder, J. (2020). Power and decision making: new directions for research in the age of artificial intelligence. Current opinion in psychology, 33, 172–176. https://doi.org/10.1016/j.copsyc.2019.07.039Campus, A. (2019). Corporate Financial Evaluation and Bankruptcy Prediction Implementing Artificial Intelligence Methods. Retrieved from: http://www.wseas.us/e-library/conferences/2006cscc/papers/534-877.pdf [Accessed 26 Sept. 2019].Griliches, Z. (1984). R&D and Innovation: Some Empirical Findings. Retrieved from: https://www.nber.org/chapters/c10047.pdfHameed, Farhan, Iqbal, W. (2018). Determinants of Firm’s open innovation performance and the role of R & D department: an empirical evidence from Malaysian SME’s. Retrieved from: https://journal-jger.springeropen.com/track/pdf/10.1186/s40497-018-0112-8Xiuqin Li, Dimitri Gagliardi & Ian Miles (2019) Innovation in R&D service firms: evidence from the UK, Technology Analysis & Strategic Management, 31:6, 732-748, DOI: 10.1080/09537325.2018.1549729Siraj, Hussain, F. (2008). ARTIFICIAL INTELLIGENCE IN MEDICAL APPLICATION: AN EXPLORATION. Retrieved from: https://www.researchgate.net/profile/Wan_Hussain_Wan_Ishak/publication/240943548_ARTIFICIAL_INTELLIGENCE_IN_MEDICAL_APPLICATION_AN_EXPLORATION/links/00b7d5292d45d674ab000000.pdfTull, E. Miller, S. (2019). The Journal of Robotics, Artificial Intelligence & Law. Retrieved from: https://www.finnegan.com/images/content/1/9/v2/197825/PUBLISHED-The-Journal-of-Robotics-Artificial-Intelligence-L.pdfLi, Gagliardi, Miles, X. (2018). Innovation in R&D service firms: evidence from the UK. Retrieved from: https://www-tandfonline-com.ez.urosario.edu.co/doi/full/10.1080/09537325.2018.1549729Ramesh, Kambhampati, Monson, A. (2004). Artificial intelligence in medicine. Retrieved from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1964229/pdf/15333167.pdfKatherine Wolf, Nakia Woodward & Richard Wallace (2013) ClinicalKey: A Review, Journal of Electronic Resources in Medical Libraries, 10:2, 79-87, DOI: 10.1080/15424065.2013.792592Alexander, A., McGill, M., Tarasova, A., Ferreira, C. and Zurkiya, D. (2019). Scanning the Future of Medical Imaging. Retrieved from: https://www-clinicalkey-es.ez.urosario.edu.co/#!/content/playContent/1-s2.0S1546144018312821?returnurl=null&referrer=nullHengstler, M., Enkel, E. and Duelli, S. (2016). Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices. Retrieved from: https://www-sciencedirect-com.ez.urosario.edu.co/science/article/pii/S0040162515004187Impedovo, D. and Pirlo, G. (2019). eHealth and Artificial Intelligence. Retrieved from: http://file:///C:/Users/anama/Downloads/eHealth-and-artificial-intelligence2019Information-SwitzerlandOpen-Access.pdfTsang, L., Kracov, D., Mulryne, J., Strom, L., Perkins, N., Dickinson, R., Wallace, V. and Jones, B. (2019). The Impact of Artificial Intelligence on Medical Innovation in the European Union and United States. Retrieved from: https://www.arnoldporter.com/-/media/files/perspectives/publications/2017/08/the-impact-of-artificial-inteelligence-on-medical-innovation.pdfMateos-Garcia, J. (2018). 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Influence of Artificial Intelligence in the firm outcomes by the innovation and R&D perspective

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