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Academic literature on the topic 'Patent Statistics'

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Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Patent Statistics"

1

Nikzad, Rashid. "Canadian patent profile: Some explorations in patent statistics." World Patent Information 35, no. 3 (September 2013): 201–8. http://dx.doi.org/10.1016/j.wpi.2013.03.001.

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Jun, Sunghae. "Patent Statistics for Technology Analysis." International Journal of Software Engineering and Its Applications 9, no. 5 (May 31, 2015): 155–64. http://dx.doi.org/10.14257/ijseia.2015.9.5.15.

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Rajeswari, A. R. "Indian patent statistics—An analysis." Scientometrics 36, no. 1 (May 1996): 109–30. http://dx.doi.org/10.1007/bf02126649.

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Jun, Sung-Hae, and Dai-Ho Uhm. "Patent and Statistics, What's the Connection?" Communications for Statistical Applications and Methods 17, no. 2 (March 31, 2010): 205–22. http://dx.doi.org/10.5351/ckss.2010.17.2.205.

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JUNG, Won-Gyo, Sang-Sung PARK, and Dong-Sik JANG. "Patent Registration Prediction Methodology Using Multivariate Statistics." IEICE Transactions on Information and Systems E94-D, no. 11 (2011): 2219–26. http://dx.doi.org/10.1587/transinf.e94.d.2219.

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Fung∗, Michael K., and William W. Chow†. "Identification of technological structures using patent statistics." Economics of Innovation and New Technology 12, no. 4 (August 2003): 293–313. http://dx.doi.org/10.1080/1043859022000000826.

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Dang, Jianwei, and Kazuyuki Motohashi. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality." China Economic Review 35 (September 2015): 137–55. http://dx.doi.org/10.1016/j.chieco.2015.03.012.

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Akkucuk, Ulas, and Mehmet Nafi Artemel. "Patent Data Visualization." International Journal of Research in Business and Social Science (2147-4478) 5, no. 3 (April 20, 2016): 66–79. http://dx.doi.org/10.20525/ijrbs.v5i3.358.

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The importance given by the governments to building a sound intellectual property infrastructure is increasing in developing countries and especially in Central Asian countries. This infrastructure is continuously improved to live up to a common standard in collaboration with government agencies, educational institutions and international agencies. In this paper, the infrastructure developments that took place in the Central Asian countries is going to be elaborated and furthermore some statistical analyses will be used in order to compare the differences and similarities between the Central Asian republics within themselves and the rest of the world. Patent based statistical data reveal a broad range of information concerning the innovative capability of countries, regions and firms. The number of patents that a country obtains in different technological fields and the change in this number over the years may provide useful information regarding the growth potential of the country and the ability to follow technological advances. For this purpose, patent statistics collected by institutions like World Intellectual Property Organization (WIPO) have been analyzed using statistical techniques. In addition to basic statistics, multidimensional scaling analysis (MDS) has been applied to the data sets.
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Carlson, Steven C., and Willy Chang. "“Obviously” a challenge: Patent survival statistics & tips." Industrial Biotechnology 5, no. 3 (September 2009): 172–73. http://dx.doi.org/10.1089/ind.2009.3.172.

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Sternitzke, Christian, Adam Bartkowski, Heike Schwanbeck, and Reinhard Schramm. "Patent and literature statistics – The case of optoelectronics." World Patent Information 29, no. 4 (December 2007): 327–38. http://dx.doi.org/10.1016/j.wpi.2007.03.003.

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Dissertations / Theses on the topic "Patent Statistics"

1

Cihan, Cengiz. "An Empirical Analysis of Knowledge Production Function: What Differs Among The OECD Countries Including Turkey." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/1757.

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Since the 1950s, economic growth has been one of the main topics of economic discipline. In this context, the sources of economic growth have been analysed by different economic theories. These theories can be decomposed into two groups, namely modern neoclassical theory and evolutionary economic theory. In the modern neoclassical economic theory, the technological progress is considered as the main determinant of the long-run economic growth. In this regard, the sources of economic growth differences among countries are analyzed by using various types of models. In the earliest studies, it is assumed that technological progress is exogenous (Solow-Swan model). Constant returns to scale and perfectly competitive market structure assumptions are the main characteristics of these studies. After the developments in the economic theory, technological progress has been taken into account in a different way by a new line of models, namely endogenous growth models. More specifically, technological progress is endogenously determined process in these models. Contrary to the previous models, increasing returns to scale, which stem from externality and the monopolistic market structure, play a significant role in endogenous growth models. We have reached to the conclusion that, although it suffers from some weaknesses, endogenous growth model proposes a more realistic explanation for the economic growth process. In the evolutionary economic theory, technological progress is also considered as the main determinant of economic growth. However, this theory deals with empirical issues by focusing on observed facts instead of constructing theoretical models, and provides both guidance and interpretation regarding technological progress. In this theory, variables and relationships that are considered have many practical implications. In that respect, its structure is very much realistic and it avoids certain logical gaps and inconsistencies. One of the aims of this thesis is to examine developments in economic theory by focusing on technological progress. For this purpose, we compare formal and evolutionary theories. Our theoretical review reveals that both the endogenous growth models in the tradition of modern neoclassical theory, and the important insights of the evolutionary economic theory help to analyze technological progress and/or economic growth. Furthermore, this thesis aims to measure technological progress. The measurement of technological progress is vital for the nations’ development strategies and the firms’ innovation policies. In this regard, we use patent statistics as a proxy of technological progress. The empirical parts of the thesis involve a number of applications of endogenous growth theory by taking into account the propositions of modern neoclassical economic theory. In this regard, the growth rate differences across countries are examined by using the frameworks of both the modern neoclassical and evolutionary theories. The results show that both theories have reasonable power to explain why growth rate differs across countries. In addition, we conclude that patenting activities rather than R&D activities more suitably represent innovative activities. Moreover, this thesis empirically tests the knowledge generation process in the framework of endogenous growth approach. We employ the knowledge production approach for this purpose. It is found that both domestic and international stocks of knowledge as measured by granted patent statistics, R&D activities, human capital and openness measures are significant factors in explaining productivity growth. Furthermore, product variety and quality improvement dimensions of technological progress are empirically analyzed by using patent statistics. It is found that both dimensions of technological progress significantly affect creation of new technologies. Finally, the findings indicate that technological capability of Turkey is far away from other developed countries covered by this study.
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de, Rassenfosse Gaétan. "Essays on the propensity to patent: measurement and determinants." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210130.

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Chapter 1 discusses the econometric pitfalls associated with the use of patent production functions to study the invention process. It then goes on to argue that a sound understanding of the invention process necessarily requires an understanding of the propensity to patent. The empirical analysis carried out in Chapter 1 seeks to explain the proportion of inventions patented – a potential metric for the propensity to patent – from an international sample of manufacturing firms.

Chapter 2 proposes a methodology to filter out the noise induced by varying patent practices in the R&D-patent relationship. The methodology explicitly decomposes the patent-to-R&D ratio into its components of productivity and propensity. It is then applied to a novel data set of priority patent applications in four countries and six industries.

Chapter 3 takes stock of the literature on the role of fees in patent systems while Chapter 4 presents estimates of the price elasticity of demand for patents at the trilateral offices (that is, in the U.S. Japan and Europe). The estimation of dynamic panel data models of patent applications suggests that the long-term price elasticity is about -0.30.


Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished

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Danguy, Jérôme. "Essays on the globalization of innovation using patent-based indicators." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209409.

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Compared to the globalized markets of goods and services, technology production has been often described as “far from globalized” and mainly concentrated in the home country of multinational enterprises. However, academics and international organizations recognize that research and development (R&D) activities are increasingly performed at the international level. In particular, the globalization of innovation is a major concern since it is at the crossroads of the rising importance of knowledge economy and the increasing international slicing of firms’ value chains. In this context, the main motivations of this thesis are to investigate the extent to which innovation takes place across national borders and to analyze the drivers of this phenomenon across countries and across industries. For this purpose, this dissertation provides new evidence on the globalization of innovation in four empirical essays using patent-based indicators.

First, the relevance of patent statistics as indicators of innovation is evaluated by studying the relationship between expenditures in R&D activities and patenting efforts. Chapter 2 decomposes this relationship at the industry level to shed light on the origins of the worldwide surge in patent applications. The empirical investigation of the R&D-patent relationship relies on a unique panel dataset composed of 18 manufacturing industries in 19 countries covering the period from 1987 to 2005, for which five broad patent indicators are developed. This study shows that patent applications at the industry level reflect not only research productivity, but also two main components of the propensity to patent which are firms’ strategic considerations: the decision to protect an invention with a patent (the “appropriability strategy”) and the number of patents filed to protect an innovation (the “filing strategy”). The comparison between the results for various patent count indicators provides also interesting insights. While some industries (computers and communication technologies) and countries (South Korea, Spain, and Poland) have experienced a drastic increase in patent applications, the ratio of priority patent applications to R&D expenditures has been generally constant. This result suggests that there has been no spurt in innovation productivity. In contrast, regional applications (filings at the United States Patent and Trademark Office or at the European Patent Office) have been increasing since the early 1990s, suggesting that the patent explosion observed in large regional patent offices is due to the greater globalization of intellectual property rights rather than a surge in research productivity. Innovative firms are increasingly targeting global markets and hence have a higher tendency to seek protection in key markets worldwide.

Chapter 3 introduces, firstly, aggregate patent-based indicators to measure the globalization of innovation production. Secondly, it describes the patterns in international technology production for a large panel dataset covering 21 industries in 29 countries from 1980 to 2005. A strong growth in the intensity of globalization of innovation is confirmed not only in terms of cross-border ownership of innovation, but also in terms of international technological collaborations. More interestingly, heterogeneity across countries and industries is observed. On the one hand, more innovative countries (or industries) do not present more globalized innovation footprint. On the other hand, the ownership of innovation is still strongly concentrated in a few countries, although its location is increasingly dispersed across the world. Thirdly, it investigates empirically two main opposing motives driving the internationalization of innovation: home-base augmenting and home-base exploiting strategies. The results show that the degree of internationalization of innovation is negatively related to the revealed technological advantage of countries across industries. Countries tend to be more technologically globalized in industrial sectors in which they are less technologically specialized. The empirical findings suggest also that countries with multidisciplinary technological knowledge are more likely to take part in international co-inventions of new technologies and to be attractive for foreign innovative firms. This aggregated patent-based analysis provides additional evidence that globalization of innovation is a means of acquiring competences abroad that are lacking at home, suggesting that home-base augmenting motives matter in the globalization of innovation production. By contrast, the internationalization of innovation does not seem to be purely market-driven since large economies are not the target of foreign innovative firms and international patenting is more related to international competitiveness of country-industry pairs than to the direction of trade flows.

While the previous chapter studies the globalization of innovation of a country with the rest of world, Chapter 4 aims at explaining who collaborates with whom in the international production of technology. In particular, the impact of technological distance between partner’s economies is investigated for a panel dataset covering international co-inventions between 29 countries in 21 industries between 1988 and 2005. The descriptive analysis highlights that the overall growth in internationalization of innovation is due to both the increase in the number of international innovative actors and the rise of the average intensity of collaboration. The empirical findings then suggest that the two main arguments related to technological distance – ‘similarity versus diversity’ – can be reconciled by taking an industry approach. Indeed, the estimation results show that the impact of technological distance is twofold on the intensity of collaborative innovation at industry level. On the one hand, the more similar the industry-specific knowledge of two countries (low technological distance within the industry), the more easily they collaborate by sharing common industrial knowledge. On the other hand, the more different their non-industry-specific knowledge (high technological distance outside the scope of the industry), the more they collaborate to gain access to broad and interdisciplinary expertise. It suggests that the relative absorptive capacity between partner’s economies and the search for novel and complementary knowledge are key drivers of the globalization of innovation. Moreover, the results confirm the moderating effect of non-technological distance factors (spatial proximity, ease of communication, institutional proximity, and overall economic ties) in cross-border innovative relationships.

The topic of Chapter 5 is the cost-benefit analysis of the creation of a new ‘globalized’ patent: the EU Patent (formerly known as Community Patent) which consists in a single patent covering the entire EU territory for both application procedure and legal enforcement after grant. The objective of this chapter is threefold: (i) simulate the budgetary consequences in terms of renewal fees’ income for the European and national patent offices; (ii) evaluate the implications for the business sector in terms of absolute and relative fees; (iii) assess the total economic impact for the most important actors of the European patent system. Based on an econometric model explaining the determinants of the maintenance rate of patents, the simulations suggest that – with a sound renewal fee structure – the EU patent could generate more income for nearly all patent offices than under the current status quo. It would, at the same time, substantially reduce the relative patenting costs for applicants. Finally, the loss of economic rents by patent attorneys, translators and lawyers, and the drop of controlling power by national patent offices elucidate further the persistence of a fragmented European patent system.


Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished

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Savin, Maxim. "National Systems of Innovation: Evidence from the Industry Level." Thesis, KTH, Samhällsekonomi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98669.

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Cihan, Cengiz. "An Empirical Analysis of Knowledge Production Function: What Differs Among The OECD Countries Including Turkey." University of Sydney, 2006. http://hdl.handle.net/2123/1757.

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Doctor of Philosophy
Since the 1950s, economic growth has been one of the main topics of economic discipline. In this context, the sources of economic growth have been analysed by different economic theories. These theories can be decomposed into two groups, namely modern neoclassical theory and evolutionary economic theory. In the modern neoclassical economic theory, the technological progress is considered as the main determinant of the long-run economic growth. In this regard, the sources of economic growth differences among countries are analyzed by using various types of models. In the earliest studies, it is assumed that technological progress is exogenous (Solow-Swan model). Constant returns to scale and perfectly competitive market structure assumptions are the main characteristics of these studies. After the developments in the economic theory, technological progress has been taken into account in a different way by a new line of models, namely endogenous growth models. More specifically, technological progress is endogenously determined process in these models. Contrary to the previous models, increasing returns to scale, which stem from externality and the monopolistic market structure, play a significant role in endogenous growth models. We have reached to the conclusion that, although it suffers from some weaknesses, endogenous growth model proposes a more realistic explanation for the economic growth process. In the evolutionary economic theory, technological progress is also considered as the main determinant of economic growth. However, this theory deals with empirical issues by focusing on observed facts instead of constructing theoretical models, and provides both guidance and interpretation regarding technological progress. In this theory, variables and relationships that are considered have many practical implications. In that respect, its structure is very much realistic and it avoids certain logical gaps and inconsistencies. One of the aims of this thesis is to examine developments in economic theory by focusing on technological progress. For this purpose, we compare formal and evolutionary theories. Our theoretical review reveals that both the endogenous growth models in the tradition of modern neoclassical theory, and the important insights of the evolutionary economic theory help to analyze technological progress and/or economic growth. Furthermore, this thesis aims to measure technological progress. The measurement of technological progress is vital for the nations’ development strategies and the firms’ innovation policies. In this regard, we use patent statistics as a proxy of technological progress. The empirical parts of the thesis involve a number of applications of endogenous growth theory by taking into account the propositions of modern neoclassical economic theory. In this regard, the growth rate differences across countries are examined by using the frameworks of both the modern neoclassical and evolutionary theories. The results show that both theories have reasonable power to explain why growth rate differs across countries. In addition, we conclude that patenting activities rather than R&D activities more suitably represent innovative activities. Moreover, this thesis empirically tests the knowledge generation process in the framework of endogenous growth approach. We employ the knowledge production approach for this purpose. It is found that both domestic and international stocks of knowledge as measured by granted patent statistics, R&D activities, human capital and openness measures are significant factors in explaining productivity growth. Furthermore, product variety and quality improvement dimensions of technological progress are empirically analyzed by using patent statistics. It is found that both dimensions of technological progress significantly affect creation of new technologies. Finally, the findings indicate that technological capability of Turkey is far away from other developed countries covered by this study.
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Righter, Emily Stewart. "Graphical and Bayesian Analysis of Unbalanced Patient Management Data." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1710.pdf.

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Schwarz, Patrick. "Prediction with Penalized Logistic Regression : An Application on COVID-19 Patient Gender based on Case Series Data." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85642.

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The aim of the study was to evaluate dierent types of logistic regression to find the optimal model to predict the gender of hospitalized COVID-19 patients. The models were based on COVID-19 case series data from Pakistan using a set of 18 explanatory variables out of which patient age and BMI were numerical and the rest were categorical variables, expressing symptoms and previous health issues.  Compared were a logistic regression using all variables, a logistic regression that used stepwise variable selection with 4 explanatory variables, a logistic Ridge regression model, a logistic Lasso regression model and a logistic Elastic Net regression model.  Based on several metrics assessing the goodness of fit of the models and the evaluation of predictive power using the area under the ROC curve the Elastic Net that was only using the Lasso penalty had the best result and was able to predict 82.5% of the test cases correctly.
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Simmonds, Mark Crawford. "Statistical methods for individual patient data meta-analysis." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595824.

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Vanier, Antoine. "The concept measurement, and integration of response shift phenomenon in Patient-Reported Outcomes data analyses : on certain methodological and statistical considerations." Thesis, Nantes, 2016. http://www.theses.fr/2016NANT1009/document.

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Les données rapportées par les patients sont maintenant fréquemment utilisées en recherche biomédicale. Ces instruments permettent la mesure de concepts subjectifs tels que la qualité de vie, les niveaux d’anxiété, de douleur, de fatigue. L’interprétation d’une différence de score au cours du temps était basée sur l’hypothèse que le sens des concepts et échelles restai stable au cours du temps dans l’esprit des individus. Cette hypothèse semble aujourd’hui dépassée. L’auto-évaluation d’un concept est maintenant comprise comme contingente de la représentation subjective qu’à un sujet du dit concept, cette représentation pouvant changer au cours du temps, surtout après avoir vécu un évènement de santé : ce phénomène est connu comme le « response shift ». Depuis la fin des années 1990s, l’investigation de ce phénomène est devenue un sujet d’intérêt majeur en psychométrie. Si des développements ont vu le jour, ce sujet reste récent et donc accompagné de débats variés que ce soit sur le plan théorique ou méthodologique. Aussi, l’objectif général de cette thèse est d’investiguer certaines problématiques méthodologiques et statistiques liées au response shift. Ce manuscrit est composé de trois travaux principaux : un état de l’art et une synthèse des travaux conduits à un niveau international depuis que le response shift est étudié, une étude pilote des performances de la procédure d’Oort (une méthode populaire de détection de response shift) par simulations et un travail théorique sur les liens entre response shift et complexité sémantique des concepts mesurés et items utilisés
Patient-Reported Outcomes are increasingly used in health-related research. These instruments allow the assessment of subjective concepts such as Health-Related Quality of Life, anxiety level, pain or fatigue. Initially, the interpretation of a difference in score over time was based on the assumption that the meaning of concepts and measurement scales remains stable in individuals’ minds over time. This assumption has been challenged. Indeed, the self-assessment of a concept is now understood as a contingency of the subjective meaning a subject has of this concept, which can change over time especially as a result of a salient medical event: the “response shift” phenomenon. Since the end of the 1990s, researches on response shift phenomenon has become of prime interest in the field of health-related research. If developments have been made, it is still a young field with various scientific debates on a theoretical, methodological and statistical level. Thus, the broad objective of this thesis is to investigate some methodological and statistical issues regarding response shift concept, detection and integration into PRO data analyses. The manuscript is composed of three main works: a state of the art and synthesis of the works conducted at an international level since response shift phenomenon is investigated, a pilot study investigating the statistical performances of the Oort’s Procedure (a popular method of response shift detection using Structural Equation Modeling) by simulations and a theoretical work about the links between response shift occurrence and semantic complexity of concepts measured and items used
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Holm, Hansen Christian. "Analysis of routinely collected repeated patient outcomes." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9556.

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Clinical practice should be based on the best available evidence. Ideally such evidence is obtained through rigorously conducted, purpose-designed clinical studies such as randomised controlled trials and prospective cohort studies. However gathering information in this way requires a massive effort, can be prohibitively expensive, is time consuming, and may not always be ethical or practicable. When answers are needed urgently and purpose-designed prospective studies are not feasible, retrospective healthcare data may offer the best evidence there is. But can we rely on analysis with such data to give us meaningful answers? The current thesis studies this question through analysis with repeated psychological symptom screening data that were routinely collected from over 20,000 outpatients who attended selected oncology clinics in Scotland. Linked to patients’ oncology records these data offer a unique opportunity to study the progress of distress symptoms on an unprecedented scale in this population. However, the limitations to such routinely collected observational healthcare data are many. We approach the analysis within a missing data context and develop a Bayesian model in WinBUGS to estimate the posterior predictive distribution for the incomplete longitudinal response and covariate data under both Missing At Random and Missing Not At Random mechanisms and use this model to generate multiply imputed datasets for further frequentist analysis. Additional to the routinely collected screening data we also present a purpose-designed, prospective cohort study of distress symptoms in the same cancer outpatient population. This study collected distress outcome scores from enrolled patients at regular intervals and with very little missing data. Consequently it contained many of the features that were lacking in the routinely collected screening data and provided a useful contrast, offering an insight into how the screening data might have been were it not for the limitations. We evaluate the extent to which it was possible to reproduce the clinical study results with the analysis of the observational screening data. Lastly, using the modelling strategy previously developed we analyse the abundant screening data to estimate the prevalence of depression in a cancer outpatient population and the associations with demographic and clinical characteristics, thereby addressing important clinical research questions that have not been adequately studied elsewhere. The thesis concludes that analysis with observational healthcare data can potentially be advanced considerably with the use of flexible and innovative modelling techniques now made practicable with modern computing power.
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Books on the topic "Patent Statistics"

1

Griliches, Zvi. Patent statistics as economic indicators: A survey. Cambridge, MA: National Bureau of Economic Research, 1990.

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United States. Patent and Trademark Office. Highlights in patent activity. [Washington, D.C.?]: U.S. Dept. of Commerce, Patent and Trademark Office, 1992.

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United States. Patent and Trademark Office. Highlights in patent activity. [Washington, D.C.?]: U.S. Dept. of Commerce, Patent and Trademark Office, 1992.

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Cockburn, Iain. Are all patent examiners equal?: The impact of characteristics on patent statistics and litigation outcomes. Cambridge, MA: National Bureau of Economic Research, 2002.

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Rafiquzzaman, Mohammed. Recent jumps in patenting activities: Comparative innovative performance of major industrial countries, patterns and explanations. Ottawa: Industry Canada, 1998.

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Group, Trilateral Statistical Working. Project A3, management information exchange: Trilateral Statistical Working Group report. Washington, DC: U.S. Patent and Trademark Office, 1998.

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Group, Trilateral Statistical Working. Project A3, management information exchange: Trilateral Statistical Working Group report. Washington, DC: U.S. Patent and Trademark Office, 1998.

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Jaffe, Adam B. Geographic localization of knowledge spillovers as evidenced by patent citations. Cambridge, MA: National Bureau of Economic Research, 1992.

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Bhattacharya, Sujit. Indian patenting activity in International and domestic patent system: Contemporary scenario. New Delhi: National Institute of Science, Technology and Development Studies, 2005.

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Rafiquzzaman, Mohammed. Recent jumps in patenting activities : comparative innovative performance of major industrial countries, patterns and explanations =: La Hausse récente des demandes de brevets et la performance des principaux pays industrialisés sur le plan de l'innovation : tendances et explications. Ottawa, Ont: Industry Canada = Industrie Canada, 1998.

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Book chapters on the topic "Patent Statistics"

1

Lambert, Nancy. "Patent statistics searching: practices and pitfalls." In Chemical Information, 141–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-75165-3_15.

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Rathod, Sandeep Kanak. "Patent Oppositions in India." In Access to Medicines and Vaccines, 151–82. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83114-1_6.

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AbstractPre-grant and post-grant oppositions filed in India by civil society and generic companies have been instrumental in visibly increasing access of drugs to the public—both in terms of earlier generic entry and also cheaper prices due to such generic competition. This paper looks at the significant pharmaceutical patent oppositions in India during the last 15 years. It focuses on some unique aspects connected to each of these oppositions and tracks how these oppositions helped in securing earlier access to generic drugs. The last part of the paper analyses patent opposition pendency statistics and notes that increasing pendency numbers, over the last few years, is a matter of deep concern as it could impact access to drugs, in future.
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de Oliveira, Meire Ramalho, Angela Emi Yanai, Diogo Soares Moreira, Cláudia Daniele de Souza, and Carlos Eduardo Gomes de Castro. "Internet of Things (IoT): Technological Indicators from Patent Analysis." In Springer Proceedings in Mathematics & Statistics, 13–22. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14973-4_2.

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Wei, Mingru, Guiping Zhang, Qiaoli Zhou, Yateng Wang, and Haihong Huang. "Statistics and Analysis of Coordination Structures in Patent Text." In Lecture Notes in Computer Science, 380–89. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14331-6_38.

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Jin, Bo, Hong-Fei Teng, Yan-Jun Shi, and Fu-Zheng Qu. "Chinese Patent Mining Based on Sememe Statistics and Key-Phrase Extraction." In Advanced Data Mining and Applications, 516–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73871-8_48.

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Zhaolian, Ouyang, Chi Hui, and Yang Guozhong. "Electronic Medical Equipment: Statistics and Analysis of Patent Data for Technology Assessment." In IFMBE Proceedings, 320–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03893-8_91.

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Xu, Danhai, Zhijian Lin, Wuyuan Zhou, Shaojun Jin, and Guochang Lv. "Carbon Dioxide Geological Utilization and Storage: A Bibliometric and Patent Analysis." In Proceedings of the 2022 International Conference on Mathematical Statistics and Economic Analysis (MSEA 2022), 1487–93. Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-042-8_215.

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Bhatt, Priyanka C., Vimal Kumar, Tzu-Chuen Lu, Rico Lee-Ting Cho, and Kuei Kuei Lai. "Rise and Rise of Blockchain: A Patent Statistics Approach to Identify the Underlying Technologies." In Communications in Computer and Information Science, 456–66. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3380-8_40.

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Atmaca, Deniz Onay. "Recent Developments in Refining Catalysts—Patent Survey Statistics for a Corporate and Geographical Outlook." In Advances in Refining Catalysis, 59–68. New York : Routledge, [2017]: CRC Press, 2017. http://dx.doi.org/10.1201/9781315370125-3.

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Braun, Veit. "Tools of Extraction or Means of Speculation? Making Sense of Patents in the Bioeconomy." In Bioeconomy and Global Inequalities, 65–84. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68944-5_4.

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AbstractOver the last few decades, Europe has seen a rise in applications for “native trait” patents on conventionally bred plants. Based on expert interviews, participant observation, patent statistics and document analysis, this chapter discusses what constitutes the (potential) value of these patents for various stakeholders. Native trait patents are a legacy of biotech plant patents from the 1980s and 1990s but follow different material, legal and economic logics. Unlike GMO patents, it would be wrong to view them as tools with which to extract surplus value from farmers. Neither, however, are they simply a means to capture investment from stock markets. There is no single business model that could explain the rush of companies to apply for patents in conventional plant breeding; therefore, patents must be understood as complex value objects that fulfil different functions for different actors and that often defy their original purpose of stimulating and protecting innovation.
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Conference papers on the topic "Patent Statistics"

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Rahmawati, Sela, Jadi Suprijadi, and Zulhanif. "Text mining factor analysis (TFA) in green tea patent data." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979456.

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Shanie, Tiara, Jadi Suprijadi, and Zulhanif. "Text grouping in patent analysis using adaptive K-means clustering algorithm." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979457.

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Tian, Yifan, and Qinghui Zhang. "Development overview of electric vehicle industry based on patent data analysis." In International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), edited by Grigorios N. Beligiannis. SPIE, 2023. http://dx.doi.org/10.1117/12.2656790.

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Zhong, Qinghong, Xiaodong Qiao, and Yunliang Zhang. "Automatic Indexing of Patent Right-claiming Document Based on Deep Learning." In 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/ammsa-18.2018.28.

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Zhang, Yading, Dan Mo, Ran Su, and Haoliang Zhong. "The Development Status of Decommissioning Technology of Nuclear Facilities: An Insight From Patents." In 2021 28th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/icone28-64203.

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Abstract The decommissioning technology of nuclear facilities has been one of the most important research directions of nuclear industry for several decades, and further enhancements are being carried out in the world. The global published patents about the decommissioning technology of nuclear facilities are investigated in this work. The technology forecasting and the development strategy of the decommissioning technology of nuclear facilities was provided from the view of patents, based on the nations, the technology field, the trend in the number of patents applications. This work will contribute to understanding the advanced developments of the decommissioning technology of nuclear facilities by a new perspective. Through quantitative statistics and content analysis, the understanding of relevant industries and technology development trend of personnel in the industry is promoted from the perspective of open patent data, a complex of technology, law and economy. Through the technology and economy behind the patent data to ensure its reliability and authenticity, this paper puts forward suggestions and prospects for the practitioners in the field of nuclear facilities decommissioning from the aspects of how to combine the research and analysis of patent situation with the development of the industry.
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Xie, Kefan, and Jingshu Du. "Research on the Independent Innovation Capability of Chinese Enterprises Based on Patent Statistics." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.1434.

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Lin, Chien-Yu, Fang-Pei Su, Kuei-Kuei Lai, Hui-Chuan Shih, and Chia-Chun Liu. "Research and Development Portfolio for the Payment FinTech Company - The Perspectives of Patent Statistics." In the 2nd International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3268808.3268823.

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Purba, Nurmitra Sari, and Rani Nooraeni. "Using LDA for Innovation Topic of Technology : Quantum Dots Patent Analysis." In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.2-8-2019.2290336.

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Konka, Boglárka, and Anita Veres. "Overview of European patents in Germany, France and Spain, with a potential application to the development of electric vehicles." In The European Union’s Contention in the Reshaping Global Economy. Szeged: Szegedi Tudományegyetem Gazdaságtudományi Kar, 2022. http://dx.doi.org/10.14232/eucrge.2022.17.

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Within the Green Deal’s ‘Accelerating the shift to sustainable and smart mobility’, vehicles with alternative propulsion systems will play a significant role, as the transport sector is responsible for one-fifth of the European Union’s CO2 emissions. Therefore, more and more governments are supporting the purchase and production of electric vehicles, as it can be one of the main tools for locally reducing fossil fuel consumption as well as reducing CO2 emissions. The analysis highlights that the three most important vehicle-producing countries (based on 2019 OICA data) from the European Union are Germany, France, and Spain. The development trajectory of these countries in the field of electromobility is presented using descriptive statistics. Sustainable development goals can be achieved by creating an innovative environment and overcoming barriers to innovation, which can be indicated, for example, by the number of patents in a given country. Therefore, a long-term time series based on patents related to electric vehicles will be explored using the database of the European Patent Office. The study describes the vehicle manufacturers with the most patents, and the main patent areas in the three countries analysed.
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Li, Y. R. "The examination of technological regime on the citations, diversification and appropriablity: Evidence from DVD Patent statistics." In 2012 IEEE 6th International Conference on Management of Innovation & Technology (ICMIT 2012). IEEE, 2012. http://dx.doi.org/10.1109/icmit.2012.6225869.

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Reports on the topic "Patent Statistics"

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Griliches, Zvi. Patent Statistics as Economic Indicators: A Survey. Cambridge, MA: National Bureau of Economic Research, March 1990. http://dx.doi.org/10.3386/w3301.

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L, Santo, and Kang K. National Hospital Ambulatory Medical Care Survey: 2019 National Summary Tables. National Center for Health Statistics (U.S.), January 2023. http://dx.doi.org/10.15620/cdc:123251.

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The Ambulatory and Hospital Care Statistics Branch of the National Center for Health Statistics (NCHS) is pleased to release the most current nationally representative data on ambulatory care visits to physician offices in the United States. Statistics are presented on physician practices as well as patient and visit characteristics using data collected in the 2019 National Ambulatory Medical Care Survey (NAMCS). NAMCS is an annual nationally representative sample survey of visits to nonfederal office-based patient care physicians, excluding anesthesiologists, radiologists, and pathologists.
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Toh, Sengwee, Kathleen Mazor, Kazuki Yoshida, Xiaojuan Li, David Arterburn, Marsha Raebel, Erick Moyneur, et al. Statistical Methods to Preserve Patient Privacy When Sharing and Analyzing Data. Patient-Centered Outcomes Research Institute (PCORI), June 2020. http://dx.doi.org/10.25302/06.2020.me.140311305.

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Esserman, Denise, Peter Peduzzi, Michael Kane, Briana Cameron, and Yu Shi. Developing New Statistical Methods for Clinical Studies Where Patients Choose Their Treatments. Patient-Centered Outcomes Research Institute (PCORI), October 2020. http://dx.doi.org/10.25302/10.2020.me.151132832.

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McCulloch, Charles, and John Neuhaus. Statistical Methods for Reducing Bias in Comparative Effectiveness Research When Using Patient Data from Doctor Visits. Patient-Centered Outcomes Research Institute® (PCORI), June 2019. http://dx.doi.org/10.25302/6.2019.me.130601466.

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Desai, Manisha, Maria Montez-Rath, Kris Kapphahn, Aya Mitani, Albee Ling, Maya Mathur, Natasha Purington, Ariadna Garcia, Vilija Joyce, and Doug Owens. Comparing Statistical Models That Predict if Patients Will Take a New Medicine as Directed. Patient-Centered Outcomes Research Institute® (PCORI), May 2020. http://dx.doi.org/10.25302/05.2020.me.13035989.

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gagne, Joshua, Moa Lee, Ajinkya Pawar, and Yaa-Hui Dong. Comparing Statistical Models That Predict if Patients Will Take a New Medicine as Directed. Patient-Centered Outcomes Research Institute® (PCORI), July 2020. http://dx.doi.org/10.25302/05.2020.me.130906274.

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Brown, Yolanda, Twonia Goyer, and Maragaret Harvey. Heart Failure 30-Day Readmission Frequency, Rates, and HF Classification. University of Tennessee Health Science Center, December 2020. http://dx.doi.org/10.21007/con.dnp.2020.0002.

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30 Day Hospital Readmission Rates, Frequencies, and Heart Failure Classification for Patients with Heart Failure Background Congestive heart failure (CHF) is the leading cause of mortality, morbidity, and disability worldwide among patients. Both the incidence and the prevalence of heart failure are age dependent and are relatively common in individuals 40 years of age and older. CHF is one of the leading causes of inpatient hospitalization readmission in the United States, with readmission rates remaining above the 20% goal within 30 days. The Center for Medicare and Medicaid Services imposes a 3% reimbursement penalty for excessive readmissions including those who are readmitted within 30 days from prior hospitalization for heart failure. Hospitals risk losing millions of dollars due to poor performance. A reduction in CHF readmission rates not only improves healthcare system expenditures, but also patients’ mortality, morbidity, and quality of life. Purpose The purpose of this DNP project is to determine the 30-day hospital readmission rates, frequencies, and heart failure classification for patients with heart failure. Specific aims include comparing computed annual re-admission rates with national average, determine the number of multiple 30-day re-admissions, provide descriptive data for demographic variables, and correlate age and heart failure classification with the number of multiple re-admissions. Methods A retrospective chart review was used to collect hospital admission and study data. The setting occurred in an urban hospital in Memphis, TN. The study was reviewed by the UTHSC Internal Review Board and deemed exempt. The electronic medical records were queried from July 1, 2019 through December 31, 2019 for heart failure ICD-10 codes beginning with the prefix 150 and a report was generated. Data was cleaned such that each patient admitted had only one heart failure ICD-10 code. The total number of heart failure admissions was computed and compared to national average. Using age ranges 40-80, the number of patients re-admitted withing 30 days was computed and descriptive and inferential statistics were computed using Microsoft Excel and R. Results A total of 3524 patients were admitted for heart failure within the six-month time frame. Of those, 297 were re-admitted within 30 days for heart failure exacerbation (8.39%). An annual estimate was computed (16.86%), well below the national average (21%). Of those re-admitted within 30 days, 50 were re-admitted on multiple occasions sequentially, ranging from 2-8 re-admissions. The median age was 60 and 60% male. Due to the skewed distribution (most re-admitted twice), nonparametric statistics were used for correlation. While graphic display of charts suggested a trend for most multiple re-admissions due to diastolic dysfunction and least number due to systolic heart failure, there was no statistically significant correlation between age and number or multiple re-admissions (Spearman rank, p = 0.6208) or number of multiple re-admissions and heart failure classification (Kruskal Wallis, p =0.2553).
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Feaster, Daniel, Hemant Ishwaran, Min Lu, and Saad Sadiq. New Statistical Methods to Assess How Patients with Different Traits Respond to the Same Treatment. Patient-Centered Outcomes Research Institute (PCORI), June 2020. http://dx.doi.org/10.25302/06.2020.me.140312907.

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Ferdosian, Hengameh, Hadi Zamanian, Sayed Ali Emami, Elahe Sedighi, Mina Moridi, and Maryam Doustmehraban. Application of artificial intelligence in prediction of cardiovascular complications in patients with diabetes mellitus type 2: A protocol of systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2021. http://dx.doi.org/10.37766/inplasy2021.10.0076.

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Review question / Objective: The aim of this systematic review is to evaluate AI-based models in identifying predictors of cardiovascular events and risk predtion in patients with diabetes mellitus type2. Condition being studied: T2DM patients have an increased risk of macrovascular and microvascular complications, lead to decreased quality of life and mortality. Considering the significance of cardiovascular complications in these patients, prediction of such events would be important. Different traditional statistical methods(such as regression) and new AI-besed algorithms are used to predict these complications in diabetic patients.
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