Prospect patents, data markets, and the commons in data-driven medicine : openness and the political economy of intellectual property rights

Scholars who point to political influences and the regulatory function of patent courts in the USA have long questioned the courts’ subjective interpretation of what ‘things’ can be claimed as inventions. The present article sheds light on a different but related facet: the role of the courts in regulating knowledge production. I argue that the recent cases decided by the US Supreme Court and the Federal Circuit, which made diagnostics and software very difficult to patent and which attracted criticism for a wealth of different reasons, are fine case studies of the current debate over the proper role of the state in regulating the marketplace and knowledge production in the emerging information economy. The article explains that these patents are prospect patents that may be used by a monopolist to collect data that everybody else needs in order to compete effectively. As such, they raise familiar concerns about failure of coordination emerging as a result of a monopolist controlling a resource such as datasets that others need and cannot replicate. In effect, the courts regulated the market, primarily focusing on ensuring the free flow of data in the emerging marketplace very much in the spirit of the ‘free the data’ language in various policy initiatives, yet at the same time with an eye to boost downstream innovation. In doing so, these decisions essentially endorse practices of personal information processing which constitute a new type of public domain: a source of raw materials which are there for the taking and which have become most important inputs to commercial activity. From this vantage point of view, the legal interpretation of the private and the shared legitimizes a model of data extraction from individuals, the raw material of information capitalism, that will fuel the next generation of data-intensive therapeutics in the field of data-driven medicine

Discovering shifts in competitive strategies in probiotics, accelerated with TechMining

[EN] Profiling the technological strategy of different competitors is a key element for the companies in a given industry, as well to technology planners and R&D strategists. The analysis of the patent portfolio of a company as well as its evolution in the time line is of interest for technology analysts and decision makers. However, the need for the participation of experts in the field of a company as well as patent specialists, slows down the process. Bibliometrics and text mining techniques contribute to the interpretation of specialists. The present paper tries to offer a step by step procedure to analyze the technology strategy of several companies through the analysis of their portfolio claims, combined with the use of TechMining with the help of a text mining tool. The procedure, complemented with a semantic TRIZ analysis provides key insights in disclosing the technological analysis of some competitors in the field of probiotics for livestock health. The results show interesting shifts in the key probiotic and prebiotic ingredients for which companies claim protection and therefore offers clues about their technology intention in the life sciences industry in a more dynamic, convenient and simple way.The authors would like to thank the contribution of the research institute IRTA, to the TRIZ company triz XXI and to Fernando Palop and their wise insights and guidance. The authors thank the usage of Search Technology s VantagePoint and IHS-Markit s Goldfire.Vicente Gomila, JM.; Palli, A.; De La Calle, B.; Artacho Ramírez, MÁ.; Jimémez, S. (2017). Discovering shifts in competitive strategies in probiotics, accelerated with TechMining. Scientometrics. 111(3):1907-1923. https://doi.org/10.1007/s11192-017-2339-5S190719231113Abbas, A., Zhang, L., & Khan, S. (2014). A literature review on the state-of-the-art in patent analysis. World Patent Information, 37, 3–13.Allen, H., Levine, T., Bandrick, M., & Casey, T. (2012). Treatment, promotion, commotion: Antibiotic alternatives in food-producing animals. Trends in Microbiology, 21(3), 114–119.Animal Task Force. (2013). Research & innovation for a sustainable livestock sector in Europe. http://www.animaltaskforce.eu/Portals/0/ATF/horizon2020/ATF%20white%20paper%20Research%20priorities%20for%20a%20sustainable%20livestock%20sector%20in%20Europe.pdf . Accessed September 4, 2016.Abramson, D. (2011). Patent strategies for life sciences companies to navigate the changing patent landscape. Journal of Commercial Biotechnology, 17, 358–364.Banan-Mwine Daliri, E., & Lee, B. H. (2015). New perspectives on probiotics and disease. Food Science and Human Wellness, 4, 56–65.Bubela, T., Gold, R., Gregory, G., Cahoy, D., & Castle, D. (2013). Patent landscaping for life sciences innovation: Toward consistent and transparent practices. Nature Biotechnology, 31, 202–206.Chih-Hung, H. (2013). Patent value assessment and commercialization strategy. Technology forecasting & Social Change, 80, 307–319.Choi, S., Yoon, J., Kim, K., Lee, J. Y., & Kim, C.-H. (2011). SAO network analysis of patents for technology trends identification: A case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells. Scientometrics, 88, 863–883.Collins, M. D., & Gibson, G. (1999). Probiotics, prebiotics, and synbiotics: Approaches for modulating the microbial ecology of the gut. American Journal of Clinical Nutrition, 69(suppl), 1052S–1057S.Ernst, H. (1998). Patent portfolio for strategic technology management. Journal of Engineering Technology Management, 15, 279–308.Ferraro, G., & Wanner, L. (2011). Towards the derivation of verbal content relations from patent claims using deep syntactic structures. Knowledge-Based Systems, 24, 1233–1244.Foligné, B., Daniel, C., & Pot, B. (2013). Probiotics from research to market: The possibilities, risks and challenges. Current Opinion in Microbiology, 16(3), 284–292.Gerken, J., & Moehrle, M. (2012). A new instrument for technology monitoring: Novelty in patents measured by semantic patent analysis. Scientometrics, 91, 645–670.Grant, R. (2006). Contemporary strategic analysis (5th ed.). ISBN 1-405-1999-3.Grant, E., Van den Hof, M., & Gold, R. (2014). Patent landscape analysis: A methodology in need of harmonized standards. World Patent Information, 39, 3–10.He, J., Yamanaka, T., & Kano, S. (2016). Mapping university receptor based on claim embodiment quantitative analysis: A study of 31 cases form the University of Tokio. World Patent Information, 46, 49–55.IHS Goldfire. www.ihsmarkit.com . Accessed November 2016.Kaushik, G. (Ed.) (2015). Applied environmental biotechnology: Present scenario and future trends. Springer. ISBN 978-81-322-2122-7.Kim, B., Miller, D., & Mahoney, J. (2016). The impact of the timing of patents on innovation performance. Research Policy, 45(2016), 914–928.Kume, H. (2010). From low power to no power through energy harvesting: Powering up the battery-free world. Nikkei Elctronics Asia; October 31, 2010; Accessed November 2011.Lanjouw, J., & Schankerman, M. (1999). The quality of ideas: Measuring innovation with multiple indicators. 7345. National Bureau for Economic Research, Cambridge, MA, USA. http://www.nber.org . Accessed September 2016.Lee, C., Kim, J., Kwon, O., & Woo, H. G. (2016). Stochastic technology life cycle analysis using multiple patent indicators. Technological Forecasting and Social Change, 106(2016), 53–64.Mogee, M. E. (1991). Using patent data for technology analysis and planning. Research-Technology Management, 34(4), 43–49.Niwa, S. (2016). Patent claims and economic growth. Economic Modelling, 54, 377–381.Noh, H., Jo, Y., & Lee, S. (2015). Keyword selection and processing strategy for applying text mining to patent analysis. World Patent Information, 42, 4348–4360.O’Callaghan, T. F., Ross, R. P., Stanton, C., & Clarke, G. (2016). The gut micorbiome as a virtual endocrine organ with implicaitons for farm and domestic animal endocrinology. Domestic Animal Endocrinology, 56, S44–S55.Pargaonkar, Y. (2016). Leveraging patent landscape analysis and IP competitive intelligence. World Patent Information, 45, 10–20.Park, H., Yoon, J., & Kim, K. (2012). Identifiying patent infringement using SAO based semantic technological similarities. Scientometrics, 90, 515–529.Park, H., Yoon, J., & Kim, K. (2013). Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining. Scientometrics, 97, 883–909.Porter, M. (2008). The five competitive forces that shape strategy. Harvard Business Review. January 2008. 1–17. Reprint R0801E. www.hbrreprints.org .Porter, A. L., & Cunningham, S. (2005). Tech Mining. Hoboken: Wiley Interscience.Porter, A., & Newman, N. (2011). Mining external R&D. Technovation, 31, 171–176.Regulation (EC) No 1831/2003 of the European Parliament and of the Council of 22 September 2003 on additives for use in animal nutrition Regulation (EC) No 1831/2003 of the European Parliament and of the Council. http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32003R1831 .Rose, C., Cronin, J., & Schwartz, R. (2007). Communicating the value of your intellectual property to Wall Street. Research Technology Management, 50(2), 36–40.Schrezenmeir, J., & De Vrese, M. (2001). Probiotics, prebiotics, and synbiotics—Approaching a definition. The American Journal of Clinical Nutrition, 73(2), 361s–364s.Soranzo, B., Nosella, A., & Filippini, R. (2016). Managing firm patents: A bibliometric investigation into the state of the art. Journal of Engineering and Technology Management, 42, 15–30.Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15, 285–305.The patent guide; A handbook for analyzing and interpreting patent data. UK Intellectual patent office.Tong, X., & Frame, D. (1994). Technological performance with patent claims data. Research Policy, 23, 133–141.VantagePoint. www.theVantagePoint.com . Accessed September 20, 2016.Verberne, S., D’hondt, E., & Oostdijk, N. (2010). Quantifying the challenges in parsing patent claims. In The 1st international workshop on Advances in Patent Information Retrieval (AsPIRe’10), Milton Keynes, UK.Verbitsky, M. (2004). Semantic TRIZ, triz-journal.com. http://www.triz-journal.com/archives/2004/ .Vicente-Gomila, J. M. (2014). The contribution of syntactic-semantic approach to the search for complimentary literatures for scientific or technical discovery. Scientometrics. doi: 10.1007/s11192-014-1299-2 .Vicente-Gomila, J. M., & Palop, F. (2013). Combining tech-mining and semantic-TRIZ for a faster and better technology analysis: A case in energy storage systems. Technology Analysis & Strategic Management, 25(6), 725–743.Wang, M., Chiu, T., & Chen, W. (2009). Exploring potential R&D collaborators based on patent portfolio analysis: The case of biosensors. In PICMET 2009 Proceedings, August 2–6, Portland, Oregon, USA.Wang, J., Lu, F., & Loh, H. (2015). A two-level parser for patent claim parsing. Advanced Engineering Informatics, 29, 431–439.Weenen, T. C., Pronker, E. S., Commandeur, H. R., & Claasen, E. (2013). Patenting in the European medical nutrition industry: Trends, opportunities and strategies. PharmaNutrition, 1, 13–21.Xie, Z., & Miyazaki, K. (2013). Evaluating the effectiveness of keyword search strategy for patent identification. World Patent Information, 35(1), 20–30.Yang, Y., & Choct, M. (2009). Dietary modulation of gut microflora in broiler chickens: A review of the role of six kinds of alternatives to in-feed antibiotics. World’s Poultry Science Journal, 65, 97–114.Yang, S.-Y., & Soo, V.-W. (2012). Extract conceptual graphs from plain texts in patent claims. Engineering Applications of Artificial Intelligence, 25, 874–887.Yoon, J., Park, H., & Kim, K. (2013). Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-bassed content analysis. Scientometrics, 94, 313–331

Strategies for reducing risk inpatent applications'analysis

Patents are a unique and exhaustive source of technological knowledge. Technical information we can find in them is not possible to obtain in other ways, such as market and economic analysis, voice of customer, etc. Patent databases also have high accessibility (since they are free available on the web) and a high level of format uniformity. This lets patent data can be electronically searched individually or together. These special features make patents a strategic source for supporting CEOs in decision making activities. At present, worldwide patent database contains over 100 million of documents. Over the last decades, the number of patent applications per year is globally raising. The global growth in patent activity can be understood as an effect due to the shift of the economy towards the knowledge-based economy paradigm. According to this, the outcomes generated by knowledge, like patents, are business products or productive assets, which can be exploited as economical goods. In such a framework, it is crucial for patent owners knowing the value of held patents to adopt the best exploitation strategy. For whom works in the patents' environment, the main difficulty relates to the proceeding the application for patent is subjected, which generally is long and complex. The application filing is the first step in an ‘obstacle course’. Dozens of events and scenarios can affect the likelihood that the application reaches the grant, some of which might cause the unavoidable fall of the application itself. The first effect of this contest is the lack of certainties and the need to adopt work strategies and assessment criteria that take the risk into account. The surge of patent filings had drastically increased the uncertainty status of patent literature. The tools and methods currently available for patent experts are not designed to manage the risk due to this uncertain scenario. IP offices of firms, patent valuation experts of banks and other expert-in-the-field people must take the risk and manage it through their own professional expertise: a difficult job which this work addresses to. Despite the high relevance and practical consequences of the uncertainty and risk related to the procedural aspects of patent applications, only few works paid attention to them. They did not give suggestions about tools or methods able to prevent or assess the level of uncertainty in patent proceeding, neither to support the applicant carrying out patent analyses in presence of high share of patent applications. This thesis is a sort of full immersion in the uncertainty of the patent application environment. From the coarsest errors anyone might do, to suggestions about most up-to-date sources of information, tools and strategies available to limit the uncertainty risk, up to an analytical system to compute the impact of procedural events on the success likelihood of the application for patent. It is a journey into the complex world of patent seen from a non-common point of view that can give useful insight to anyone working in the field. Chapter 1 presents an overview on the currently available valuation methods for patents and the limitation they have in working with uncertainty due to patent applications. Chapter 2 is an in-depth discussion about issues related to the transformations the text of patent application may undergo during the PCT and EPC proceedings. Chapter 3 expounds a wide analysis that carried out in EP patent register to make an infographic about the success-rate of EP applications in grant and post grant proceedings. Chapter 4 gives operative indications about building a business intelligence to assess the background into which positioning a patent application. Finally, the Chapter 5 deals with the extraction of information about the market structure from patent data. In presence of patent thicket, dominant positions of main incumbent competitors might hindrance the access to the market of new entrants

Strategies for reducing risk inpatent applications'analysis

Patents are a unique and exhaustive source of technological knowledge. Technical information we can find in them is not possible to obtain in other ways, such as market and economic analysis, voice of customer, etc. Patent databases also have high accessibility (since they are free available on the web) and a high level of format uniformity. This lets patent data can be electronically searched individually or together. These special features make patents a strategic source for supporting CEOs in decision making activities. At present, worldwide patent database contains over 100 million of documents. Over the last decades, the number of patent applications per year is globally raising. The global growth in patent activity can be understood as an effect due to the shift of the economy towards the knowledge-based economy paradigm. According to this, the outcomes generated by knowledge, like patents, are business products or productive assets, which can be exploited as economical goods. In such a framework, it is crucial for patent owners knowing the value of held patents to adopt the best exploitation strategy. For whom works in the patents' environment, the main difficulty relates to the proceeding the application for patent is subjected, which generally is long and complex. The application filing is the first step in an ‘obstacle course’. Dozens of events and scenarios can affect the likelihood that the application reaches the grant, some of which might cause the unavoidable fall of the application itself. The first effect of this contest is the lack of certainties and the need to adopt work strategies and assessment criteria that take the risk into account. The surge of patent filings had drastically increased the uncertainty status of patent literature. The tools and methods currently available for patent experts are not designed to manage the risk due to this uncertain scenario. IP offices of firms, patent valuation experts of banks and other expert-in-the-field people must take the risk and manage it through their own professional expertise: a difficult job which this work addresses to. Despite the high relevance and practical consequences of the uncertainty and risk related to the procedural aspects of patent applications, only few works paid attention to them. They did not give suggestions about tools or methods able to prevent or assess the level of uncertainty in patent proceeding, neither to support the applicant carrying out patent analyses in presence of high share of patent applications. This thesis is a sort of full immersion in the uncertainty of the patent application environment. From the coarsest errors anyone might do, to suggestions about most up-to-date sources of information, tools and strategies available to limit the uncertainty risk, up to an analytical system to compute the impact of procedural events on the success likelihood of the application for patent. It is a journey into the complex world of patent seen from a non-common point of view that can give useful insight to anyone working in the field. Chapter 1 presents an overview on the currently available valuation methods for patents and the limitation they have in working with uncertainty due to patent applications. Chapter 2 is an in-depth discussion about issues related to the transformations the text of patent application may undergo during the PCT and EPC proceedings. Chapter 3 expounds a wide analysis that carried out in EP patent register to make an infographic about the success-rate of EP applications in grant and post grant proceedings. Chapter 4 gives operative indications about building a business intelligence to assess the background into which positioning a patent application. Finally, the Chapter 5 deals with the extraction of information about the market structure from patent data. In presence of patent thicket, dominant positions of main incumbent competitors might hindrance the access to the market of new entrants

Patent data driven innovation logic

Innovation research is conventionally conducted with creativity techniques such as TRIZ, Mind Mapping, Brainstorming, etc. (Dewulf, Baillie 1998). Patent research is typically used to research novelty or prior art, and legal studies. This thesis is at the intersection of creativity techniques, and patent data analysis. It describes how to utilise patent data for distilling Innovation Logic and conducting innovation research. Using the patent research tool PatentInspiration (© AULIVE Software NV), the 4 different stages of the Innovation Logic approach have been subjected to text analysis in patent literature. The specific text patterns were identified and documented on several case studies, with one case study across the whole thesis: the toothbrush. The opportunities and limitations of Patent Data Driven Innovation Research have been documented and discussed. This methodology has been demonstrated within a proposed structural approach to problem solving, technology marketing and innovation research. Furthermore, the potential of artificial idea generation and artificial creativity was examined and debated for the purpose of computer aided creativity. This thesis examines and confirms three claims: CLAIM 1: PROPERTIES AND FUNCTIONS CAN BE ADJECTIVES AND VERBS IN PATENT LITERATURE CLAIM 2: PATENT DATA ANALYSIS AUGMENTS THE FULL INNOVATION LOGIC PROCESS CLAIM 3: ARTIFICIAL INNOVATION METHODS CAN BE FUELED BY PATENT DATA Patent data can be text mined, acting as a global brain consisting of over 100 million invention documents. It is possible to use this existing data to reverse engineer thinking methodologies, allowing scientists and engineers to solve new problems, invent new products or processes, or find new markets for existing technologies. Patent Data Driven Innovation Logic will demonstrate a systematic innovation approach that combines the force of contemporary data mining methods on patent literature, with a structured innovation research methodology.Open Acces

The combination of the disciplines of Techmining and semantic TRIZ for better and faster analyzing technology evolution

Tesis por compendioThe purpose of the present thesis is to explore and to demonstrate how the combination of two methodological approaches, text mining plus the systemic vision of TRIZ empowered by semantics, can bring a larger and more comprehensive analysis of the evolution of a technology. Both approaches had been not combined before the first of the four papers constituents of the present thesis based in a compendium of publications. However, this combination applied to the evolution of technologies is increasingly being published in the scientific literature. Such combination shows a second benefit in the form of an improvement in accessing and connecting knowledge from disparate scientific literatures in a systematic manner. The common element in all these papers is the use of the technology mining approach, 'techmining', the application of text mining techniques based on technology management knowledge, combined with the use of semantic TRIZ, the advantage of syntactic applied to the systemic vision of TRIZ. These papers show that a better analysis of evolving technologies, e.g. by profiling technologies from a systemic point of view or, a better access to knowledge, e.g. by semantically connecting concepts with meaning, can be achieved. The research on applying the combination of these approaches to scientific and technological information analysis explores the advantages and new possibilities for technology trends assessment as well as the semantic connection of concepts which represents a change in the way information research can be done. The different applications of the aforementioned combination are explored by means of the here presented articles. The structure followed in this research is the collection of three papers published in international academic journals indexed in the most prestigious databases and one chapter in a proceedings book of an international congress. The attached articles show the research undertaken to demonstrate the aforementioned benefits of the proposed combination. Despite it can be found many methods and approaches about the assessment of the evolution of technologies, distributed across the literature, there is still a need to better understand which technologies may emerge, which may evolve faster and at what pace can they reach the market. The combination of the techmining approach and the semantic TRIZ approaches allows understanding the trends enriched with a systemic vision of the links, functions, and influences of constituent and enabling elements of a technology. Such systemic link of elements with its components and ecosystem also allows for a multi-dimensional view of a technology and further reduces the uncertainty to preview the progress of a technology. The papers presented in this dissertation are based on the combination of the TRIZ methodology, the techmining approach and the semantic TRIZ approach, applied to different technologies in different domains, to proof the advantages and implications of the combination. The articles try the different interactions of the combined approaches, applied to the assessment of different technologies, such as lithium batteries for the electric car, a medical case linked to a disease known as Meniére's Disease, the prognosis of prostate cancer, and the usage of probiotics as substitutes of antibiotics in the animal health. The wide range of technologies was selected to show the clear benefits of either combining the two approaches or applying predominantly one of them in the case of the Meniére's disease article. That difference in the nature of technologies also helped to better understand the systemic point of view of the technology, exploring new applications based on the general system theory from Bertalanffy as well as other related approaches about technologies.El propósito de la presente tesis es la exploración y la demostración de la combinación de dos enfoques metodológicos, la minería de textos y la visión sistémica de TRIZ reforzada con la semántica, pueden aportar un mayor y mas exhaustivo análisis de la evolución de una tecnología. Ambos enfoques no habían sido combinados antes del primero de los cuatro artículos que representan esta tesis por compendio de publicaciones, aunque dicha combinación ha sido crecientemente publicada en la literatura científica, para multiples propósitos desde entonces. Un segundo aporte proporcionado por esta combinación es la mejora de la capacidad de acceso al conocimiento y cómo ello supone un avance para el descubrimiento a través de literaturas no relacionadas "disparate literature discovery" de una forma metódica y científica. El elemento común en los artículos aquí presentados es el aprovechamiento de techmining, esto es, la minería de textos con base en la gestión tecnológica, por ejemplo mediante el perfilado de tecnologías, junto al enfoque de la metodología TRIZ potenciada por el análisis sintáctico y semántico, esto es, mediante la conexión semántica de conceptos, para un análisis más completo de la evolución tecnológica, proporcionando al mismo tiempo un acceso más racional al conocimiento. La investigación sobre la aplicación de la citada combinación al análisis de información científica y tecnológica explora las ventajas y nuevas posibilidades en la evaluación del avance de la tecnología, así como la conexión semántica de conceptos que representa nuevas posibilidades en la forma en que la investigación textual puede hacerse. La estructura de la investigación aquí presentada se muestra a través de los artículos publicados en revistas internacionales de alto impacto y el capítulo de los 'proceedings' de un congreso internacional. Dichos artículos muestran la investigación llevada a cabo para demostrar los beneficios mencionados de la combinación propuesta. A pesar de la gran actividad de investigación y de la existencia de varios enfoques para la prospectiva y la previsión tecnológica presentes en la literatura científica, existe aún la necesidad de entender qué tecnologías pueden emerger, pueden evolucionar más rápido y a qué velocidad pueden llegar al mercado. La combinación de los enfoques de minería tecnológica o techmining y TRIZ semántico permite entender las tendencias de una tecnología dada, enriquecida con una visión de su sistémica, y teniendo en cuenta las conexiones de sus elementos y las influencias de sus elementos constituyentes. Tal conexión entre los components y su entorno permite una vision multidimensional de la tecnología reduciendo más aún la incertidumbre en la previsión de la evolución de una tecnología. Los artículos presentados en esta tesis son aplicaciones y exploraciones de la combinación de mencionada, a diferentes tecnologías de diversos ámbitos muy dispares entre sí, con el fin de demostrar sus ventajas e implicaciones. Los artículos tratan las diferentes interacciones entre ambos enfoques de trabajo, aplicados a tecnologías como baterías de litio para los vehículos eléctricos, un caso médico ligado a una dolencia como el síndrome de Méniere, a la prognosis del cáncer de próstata y al uso de probióticos en la alimentación animal como sustitución de los antibióticos. Este amplio rango de tecnologías han sido seleccionados para mostrar las ventajas, de forma más objetiva, de la combinación de ambos enfoques o con predominancia de alguno en particular, como es el caso del artículo explorando el síndrome de Méniere. Estas exploraciones permiten también entender mejor el punto de vista sistémico de una tecnología, descubriendo nuevas aplicaciones basadas en la teoría general de sistemas de Bertalanffy así como en otros enfoques relacionados.El propòsit de la present tesi és l'exploració i la demostració de la combinació de dos enfocaments metodològics, la minería de textes i la visió sistémica de TRIZ, reforçada amb la sintáctica i la semántica, mostrant que poden oferir un abast més gran i més holístic en l'enteniment de l'evolució d'una tecnología. Tots dos enfocaments no habían estat combinats abans del primer article dels quatre que composen aquesta tesi, però creixentment combinat dins la literatura científica per a múltiples propostes des de la primera publicació. Una segona aportació proporcionada per aquesta combinació és la millora de la capacitat d'accés al coneixement, i de com això suposa un avanç en l'àrea de recerca a traves de literatures no relacionades "disparate literature discovery" d'una forma metòdica i científica. L'element comú en els articles presentats en aquesta tesi és l'aprofitament de la mineria de textos amb base en la gestió tecnològica, 'techmining', per exemple mitjançant el perfilat de tecnologies, al costat de l'enfocament de la metodologia TRIZ potenciada per l'anàlisi sintàctica i semàntica, mitjançant la conexión semántica de conceptes, per assolir un anàlisi més complet de l'evolució tecnològica, així com per a garantir un accés més racional al coneixement. La investigació de l'aplicació de la combinació dels dos enfocaments a l'anàlisi d'informació científica i tecnològica realizat, exploren els avantatges i noves possibilitats en l'avaluació de l'avanç de tecnologies, així com la conexión de conceptes uqe representa noves possibilitats en la forma en què la investigació textual pot fer-se. L'estructura de la investigació ací presentada es mostra a través dels articles publicats i el capítol dels 'proceedings' d'un congrés internacional. Aquests articles mostren la investigació duta a terme per demostrar els beneficis esmentats. Tot i la gran activitat de recerca i enfocaments per a la prospectiva i la previsió tecnològica existents a la literatura científica, existeix encara la necessitat d'entendre quines tecnologies poden emergir, poden evolucionar més ràpid i a quina velocitat poden arribar al mercat. La combinació dels enfocaments de mineria tecnològica o 'techmining' i TRIZ semàntic permet entendre les tendències d'una tecnologia donada, amb una visió del seu sistema, les connexions dels seus elements i les influències dels elements constituents. Els articles presentats en aquesta tesi són aplicacions i exploracions de la combinació de la metodologia TRIZ, la seva potenciació mitjançant la semàntica i el techmining a diferents tecnologies de diversos àmbits, alguns molt dispars entre si, per tal de demostrar les seves avantatges i implicacions. Els articles tracten les diferents interaccions entre els dos enfocaments de treball, aplicats a tecnologies com bateries de liti per als vehicles elèctrics, un cas mèdic lligat a una malaltia com la síndrome de Ménière, a la prognosi del càncer de pròstata i en alimentació, a l'ús de probiòtics en l'alimentació animal com a substitució dels antibiòtics. Aquest ampli rang de tecnologies han estat seleccionats per mostrar els avantatges de forma més objectiva, de la combinació de tots dos enfocaments o amb predominança d'algun en particular, com és el cas de l'article explorant la síndrome de Ménière. Aquestes exploracions permeten també entendre millor el punt de vista sistèmic d'una tecnologia, descobrint noves aplicacions amb base en la teoria general de sistemes de Bertalanffy així com altres treballs relacionats.Vicente Gomila, JM. (2017). The combination of the disciplines of Techmining and semantic TRIZ for better and faster analyzing technology evolution [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/89088TESISCompendi

Cerebrovascular segmentation from MRA images

There is provided a method of processing a cerebrovascular medical image, the method comprising receiving magnetic resonance angiography (MRA) image associated with a cerebrovascular tissue comprising blood vessels and brain tissues other than blood vessels; segmenting MRA image using a prior appearance model for generating first prior appearance features representing a first-order prior appearance model and second appearance features representing a second-order prior appearance model of the cerebrovascular tissue, wherein current appearance model comprises a 3D Markov-Gibbs Random Field (MGRF) having a 2D rotational and translational symmetry such that MGRF model is 2D rotation and translation invariant; segmenting MRA image using current appearance model for generating current appearance features distinguishing blood vessels from other brain tissues; adjusting MRA image using first and second prior appearance features and current appearance futures; and generating an enhanced MRA image based on said adjustment. There is also provided a system for doing the same. Application US16/159,790 events 2018-10-15 Application filed by Zayed University 2018-10-15 Priority to US16/159,790 2018-10-15 Assigned to Zayed University 2020-04-16 Publication of US20200116808A1 2020-09-08 Application granted 2020-09-08 Publication of US10768259B2 Status Active 2039-03-02 Adjusted expiratio

Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model

Early identification of emergent topics is of eminent importance due to their potential impacts on society. There are many methods for detecting emerging terms and topics, all with advantages and drawbacks. However, there is no consensus about the attributes and indicators of emergence. In this study, we evaluate emerging topic detection in the field of artificial intelligence using a new method to evaluate emergence. We also introduce two new attributes of collaboration and technological impact which can help us use both paper and patent information simultaneously. Our results confirm that the proposed new method can successfully identify the emerging topics in the period of the study. Moreover, this new method can provide us with the score of each attribute and a final emergence score, which enable us to rank the emerging topics with their emergence scores and each attribute score