United States Patent Research Articles

The Tenuous Relationship Between Working From Home and Job Performance

The COVID-19 crisis has led to massive increases in working from home (WFH), compelling many individuals to telecommute in challenging circumstances. Further, the strong emphasis on WFH is likely to continue after the pandemic. In this study, we examine the impact of WFH on job performance before and during the COVID-19 crisis. Using longitudinal data on patent examiners at the United States Patent and Trademark Office, we assess the WFH efficacy under various conditions, such as self-selection into WFH, degree of WFH, transition to a WFH mandate, and the passage of time during that mandate. Results show an overall detrimental impact of the WFH mandate on job performance. Even individuals who initially opted into WFH can suffer job performance reduction when circumstances worsen and presumably due to prior expectations for the WFH setting being unmet. However, we also find that such performance decline begins to recover over time, suggesting individual and organizational learning. Although the pandemic is an extreme example of unfavorable circumstances, our study suggests a more tenuous relationship between WFH and job performance than emerges in literature generally focused on voluntary WFH and favorable context.

Notes on the use of trademark registrations as an innovation metric for the creative and cultural industries: an analysis based on USPTO data

The creative and cultural industries have been gaining importance in the generation and diffusion of value in economies over the last decades. However, there is still a gap regarding the definition of variables that could be used as production and innovation indicators for this sector. As such, we propose the use of trademark registers as indicators of the production and introduction of new goods and services in segments related to this sector. First, we provide a descriptive analysis of United States Patent and Trademark Office (USPTO) trademark registration data throughout the twentieth century. This analysis allows us to see that the trademarks registered in segments aligned with the creative and cultural industries have shown strong expansion, especially since the 1980s, which can be related to the technological and economic changes observed in the global market in this period. This movement is observable especially among the most technology-intensive segments, such as the production of software, digital games and music. Second, we analyse the factors associated with trademark registration in the period covered using ordinary least square estimates. The main results show that patent registration and revenue (a proxy for size) are strongly associated with trademark registration for companies in the creative economy. On the other hand, location in a developed country is not a determinant of the registration of trademarks in the sector, in contrast to the results obtained for the whole set of firms. In the case of low-tech firms in the creative economy, only revenue explains the registration of trademarks.

Biological patent thickets and delayed access to biosimilars, an American problem.

Our study seeks to determine whether patent thickets covering biologic drugs are responsible for delayed biosimilar market entry. We compare patent assertions against the same biosimilar drugs across three countries. On average nine to twelve times more patents were asserted against biosimilars in the United States than in Canada and the United Kingdom. Biosimilars also enter the Canadian and UK markets more quickly than they do in the United States following regulatory approval. Later market entry is not a problem when the brand name drug company is asserting high quality patents (i.e. patents covering significant advances). Consequently, we drilled down into the U.S. patent portfolio of one major biologic, Abbvie's Humira drug, and found that it was made up of roughly 80% non-patentably distinct (duplicative) patents linked together by terminal disclaimers, which is permitted under United States Patent and Trademark Office (USPTO) rules. In contrast, there were far less non-duplicative European patents that covered Humira. Patent thickets can allow brand name drug companies to delay biosimilar entry by relying on the high cost of challenging many duplicative patents instead of the quality of their underlying patents. Accordingly, we suggest several policy interventions that may thin these biologic patent thickets.

WHO invents what? Women’s participation in patenting activity in Spain

PurposeRecent years have seen increased participation by women in Science and Technology activities, but parity with men remains a distant goal. This paper provides a framework for improving knowledge on the dynamics of women’s contributions to innovation, as measured through their contributions as inventors.Design/methodology/approachAnalysis was conducted using data from the United States Patent and Trademark Office (USPTO) database, covering over 40 years from 1976 to 2019. The study provides a breakdown of women’s inventiveness/innovation by technology area, which permits analysis of whether female inventors tend to work individually or as part of a team, as well as analysis of the effects of international networks.FindingsSpecific data have been analyzed around innovative activity by women in Spain, providing new insights on gender gaps. Key findings include those recent increases in inventions by women (as measured through patents) have occurred mostly via participation in internationally connected mixed-gender teams. Furthermore, the inventive creativity of women is found to be sector-biased and framed mainly in the chemical sector.Originality/valueThere are no similar contributions using USPTO data for Spanish inventions. This is an original paper that emphasizes the potential of collaborative networks as key driving mechanisms for the reduction of gender gaps and for the larger integration of women into innovation activities, with potential implications for stakeholders at both firm and governmental levels.

Moo-re Gene-edited Animals Get Regulatory Clearance: U.S. FDA Approves Genetically Engineered Cattle for Human Consumption

Moo-re Gene-edited Animals Get Regulatory Clearance: U.S. FDA Approves Genetically Engineered Cattle for Human Consumption

The Race to Replace PDE5i: Recent Advances and Interventions to Treat or Manage Erectile Dysfunction: Evidence from Patent Landscape (2016-2021).

For a few decades, globally, erectile dysfunction (ED) has become more prominent even in young adults and represents a mounting health concern causing a significant effect on men’s quality of life. There is an expectation that by the end of 2025, the number of ED cases can rise to 322 million. We aimed to comprehensively analyze the scientific output of scholarly articles and studies in the field of ED (2016–2021). Data from scholarly articles were collected using Pubmed, and clinical trials-related information was accessed from the clinical trials website. An extensive patent search was conducted using databases such as USPTO (United States patent and trademark office) and EPO (European patent office), WIPO (World Intellectual Property Organization), etc. Owing to the high market value of ED drugs, considerable interest was attained to grab the opportunities. The race to replace the phosphodiesterase type 5 inhibitor (PDE5 inhibitor-PDE5i) can be identified as evident from the significant number of patents filed and the inventions cleared with clinical trials. Some other intriguing interventions are identified for ED treatment but have yet to gain public acceptance. The current analysis confirms the overall evolution and unexplored corners of research on ED treatment strategies with a current global projection.

Firm performance and information security technology intellectual property

The appropriate valuation of information security (InfoSec) intellectual property (IP) is of interest to both business scholars and investors. This topic is important because InfoSec IP is a complementary knowledge resource that can complement a firm's existing and new products, services, business models, and operations. This paper attempts to understand the marginal effects of having additional InfoSec IP on a firm's performance in terms of return on investment and market capitalization. We collected objective InfoSec IP data from the United States Patent Office, the United States Copyright Office, and Compustat. Specifically, our data includes various types of IP, including patents, copyrights, and patent portfolios. We exclude IT-security firms in this study because we are interested in the effect of InfoSec IP on non-IT security firms. We include panel regression models using fixed effects that test the interplays between the various types of InfoSec IP and a firm's performance. In addition, we conduct generalized moment method and Heckman correction model analyses to alleviate potential endogeneity and sampling biases. Our results suggest that InfoSec IP is positively related to both return on investment and market capitalization. Further, we find that diverse InfoSec IP portfolios strengthen the effects of a firm's InfoSec patents and copyrights on market capitalization.

Analysis of Patent and Regulatory Exclusivity for Novel Agents in China and the United States: A Cohort Study of Drugs Approved Between 2018 and 2021

Patent and regulatory exclusivity shall constitute incentives for pharmaceutical companies to develop new drugs. This study aims to investigate the differences in the patent term extension (PTE) and regulatory exclusivity between China and the United States, and to evaluate their potential impact on the market exclusivity period of novel drugs. Small-molecule novel drugs with their first indication approved in China and the United States between 2018 and 2021 were evaluated regarding their PTE and regulatory exclusivity. The PTE length of the China-approved drugs was calculated by simulation, whereas that of the US-approved drugs was extracted from the United States Patent and Trademark Office. Thirty-two and 107 novel drugs approved in China and the United States, respectively, were included in the study. The PTE length of the US-approved drugs calculated by the China-PTE method was significantly longer than that calculated by the US-PTE method. Patent extensions should be granted for 91% of new drugs in China and 82% in the United States. The simulated median PTE length of novel drugs approved in China was significantly higher than that of the United States (5.0 vs. 2.9years, P<0.05). It can be expected that the implementation of the PTE policy in China would significantly extend the period of market exclusivity for novel drugs similar to that of the United States. China should fully evaluate the potential impact of the PTE policy on the market exclusivity of novel drugs and provide better incentives to the development of novel drugs in addressing unmet clinical needs when developing its regulatory exclusivity policy.

Talents and Cultures: Immigrant Inventors and Ethnic Diversity in the Age of Mass Migration

Abstract We investigate the importance of co-ethnic networks and diversity in determining immigrant inventors’ settlements in the United States by following the location choices of thousands of them across counties during the Age of Mass Migration. To do so, we combine a unique United States Patent and Trademark Office historical patent dataset on immigrants who arrived as adults with Census data and exploit exogenous variation in both immigration flows and diversity induced by former settlements, WWI, and the 1920s Immigration Acts. We find that co-ethnic networks play an important role in attracting immigrant inventors. Yet, we also find that immigrant diversity acts as an additional significant pull factor. This is mainly due to externalities that foster immigrant inventors’ productivity.

Predicting Institution Outcomes for Inter Partes Review (IPR) Proceedings at the United States Patent Trial &amp; Appeal Board by Deep Learning of Patent Owner Preliminary Response Briefs

A key challenge for artificial intelligence in the legal field is to determine from the text of a party’s litigation brief whether, and why, it will succeed or fail. This paper shows a proof-of-concept test case from the United States: predicting outcomes of post-grant inter partes review (IPR) proceedings for invalidating patents. The objectives are to compare decision-tree and deep learning methods, validate interpretability methods, and demonstrate outcome prediction based on party briefs. Specifically, this study compares and validates two distinct approaches: (1) representing documents with term frequency inverse document frequency (TF-IDF), training XGBoost gradient-boosted decision-tree models, and using SHAP for interpretation. (2) Deep learning of document text in context, using convolutional neural networks (CNN) with attention, and comparing LIME and attention visualization for interpretability. The methods are validated on the task of automatically determining case outcomes from unstructured written decision opinions, and then used to predict trial institution or denial based on the patent owner’s preliminary response brief. The results show how interpretable deep learning architecture classifies successful/unsuccessful response briefs on temporally separated training and test sets. More accurate prediction remains challenging, likely due to the fact-specific, technical nature of patent cases and changes in applicable law and jurisprudence over time.

The Role of Articles in Science–Technology Relationship: A Topic Analysis of Non-patent Literature (NPL) References

Patents with non-patent literature (NPL) references indicate how the link between science and technology interact. Using topic modeling, this paper investigated the thematic relationship between patents and their cited articles in the field of Nanotechnology. For this purpose, patents in the field of nanotechnology (IPC Class: B82) were obtained from the United States Patent and Trademark Office from 1985 to 2019. Then, NPL references listed in “Other References” section of the patents was extracted and abstract of the NPL references was retrieved from Scopus database. R software, topic modeling, and Latent Dirichlet Allocation algorithm were used to analyze the data. Results showed that most of the subclasses in Nanotechnology use few NPL references and are more dependent on patents. In total, NPL references account for only 36% of patent citations. The topics of the NPL references in this field (nanotechnology) belonged to six categories: Physics, Electricity, Chemistry, Cellular and Molecular Biology, Medicine, and Nanotechnology. Consequently, it seems that nanotechnology patents are more technology-driven, and a medium to low relationship exists between science and nanotechnology. The topic modeling of NPL references uncovered that nanotechnology patents have been more influenced by non-nano scientific.

White Whale, Black Swan

White Whale, Black Swan

The study of innovation and absorptive capacity of BRICS countries by using multiple regression analysis

Objective of the study: This research aims to explore the diverse impacts of national innovation systems of BRICS countries by indicating the key elements and systems aspect, how these aspects have committed to the running of the whole systems and interpreted inside the economic development of these nations.Methodology/approach: Data were collected from the World Bank (WDI), United Nations Educational, Scientific and Cultural Organization (UNESCO), United State Patent and Trade office (USPTO), and World Intellectual Property Organization (WIPO) for Brazil, Russia, India, China and South Africa (BRICS) countries. Data used for following research are time series, annual data from 1999-2014. The multi-regression analysis was completed with utilizing the Statistical package for the Social Science (SPSS).Originality/Relevance: We intend at devoting to the research literature and policy by producing quantitative based proof of the framework that connects the comprehensive element of innovation system to economic system for a longtime.Main results: The findings showed the degree to which components of the National innovation system (NIS), depend on one another for Brazil, Russia, India, China and South Africa (BRICS) , in this regard, any changes in one indicator can effect on other indicators in the system.Theoretical/methodological contributions: Our research is based on the conceptual analyses which draw from the existing literature. It is based on a model to evaluate the dynamics of innovation capacity, absorptive capacity impact and robustness of the economic development.Social /management contributions: Our results have significant implication for policy makers.

Investigating emerging hydrogen technology topics and comparing national level technological focus: Patent analysis using a structural topic model

Hydrogen technology has recently attracted great attention as a new energy technology with a potential to transform existing energy systems. However, since hydrogen technology is based on a concept encompassing a broad range of topics, such as hydrogen production, storage, distribution, and utilization, it is difficult for individual field experts to analyze it from an integrated viewpoint. In this study, we used a semiautomated, unsupervised learning approach for patent data analysis to identify specific technology topics in various fields of hydrogen technology and to analyze the technological focus of key countries. Thus, we collected 17 281 hydrogen technology patents from the last decade (2010–2019) from the United States Patent and Trademark Office (USPTO) and input the text in the title and abstract of the collected patents along with their metadata to a structural topic model. Consequently, we identified various hydrogen technology topics estimated based on the co-occurrence pattern of words within patents and represented as probabilistic word distribution. Furthermore, the metadata of the collected patents were used to identify topics that were newer or more impactful and appeared more frequently in patents from a certain country. After identifying technology topics, we also estimated the technology maturity rate (TMR) of each topic to measure its remaining potential. Among the 40 latent technology topics identified from the collected patents, 11 topics showed increasing proportion over time (new and trending) and five topics were highly cited by other patents (impactful). Furthermore, based on the analysis results, implications were presented for hydrogen research and development (R&D) strategy by (1) comparing the technology portfolios of key countries, (2) performing a technology correlation analysis of the identified hydrogen technology topics, and (3) proposing a decision framework for policymakers to categorize identified topics. We found that the primary technological focus was on fuel cell technologies for South Korea and Japan whereas hydrogen production technologies for France and the United States. Furthermore, technological rivalry patterns between key countries may differ notably depending on their specific technology topics or fields, highlighting the need for considering such aspects in developing R&D strategies. Finally, based on the proposed decision framework, we identified which technology topic to continue to focus on and consider easier expansion.

Capturing information on global knowledge flows from patent transfers: An empirical study using USPTO patents

In the global open innovation environment, one of the main characteristics of the knowledge-based economy is to pay more attention to the importance of global knowledge flows. This paper investigates global knowledge flows from the perspective of patent transfers, which can not only reflect the patents' economic value but also explore explicit and tacit knowledge flows comprehensively. This paper begins with the premise that global knowledge flows include the internal absorption of knowledge (IAK), knowledge outflows (KOFs) and knowledge inflows (KIFs) based on a dataset derived from United States Patent and Trademark Office (USPTO) during 2002 and 2016. Then, a global knowledge flow network is constructed by integrating patent transfer analysis and social network analysis. Our results show that more and more inventors and assignees are involved in the global knowledge flow network, China and India's ranking in the list of knowledge creators and users rises rapidly, cross-border knowledge flows will become a new trend; the rapid development of G06F (electric digital data processing), H04L (transmission of digital information) and other technological fields has accelerated the global knowledge flows; at present, the United States is the largest net knowledge inflow participant, the United Kingdom is the largest net knowledge outflow participant; the characteristics of a small-world effect in the cross-border knowledge flow network composed of 35 major participants become increasingly obvious. Our findings have clear policy implications. Establishing a global knowledge flow network is needed in order to promote global knowledge transfers, absorption and sharing.

Editorial introductions.

Current Opinion in Cardiology was launched in 1985. It is part of a successful series of review journals whose unique format is designed to provide a systematic and critical assessment of the literature as presented in the many primary journals. The field of cardiology is divided into 14 sections that are reviewed once a year. Each section is assigned a Section Editor, a leading authority in the area, who identifies the most important topics at that time. Here we are pleased to introduce the Section Editors for this issue. SECTION EDITORS Subodh VermaSubodh VermaDr Subodh Verma is an internationally renowned cardiac surgeon-scientist and Professor at the University of Toronto, Canada. He is the Canada Research Chair in Cardiovascular Surgery and a past recipient of the Howard Morgan Award for Distinguished Achievements in Cardiovascular Research and the Royal College of Physicians and Surgeons of Canada Gold Medal in Surgery. He previously served as the Canada Research Chair in Atherosclerosis from 2007–2017. He is an appointee of the American Association of Thoracic Surgeons (AATS) and a member of the College of New Scholars, Artists and Scientists, Royal Society of Canada. According to Google Scholar in December 2020, Dr Verma has an h-index of 107 and his work has been cited over 58,000 times. Dr Verma has published extensively in prestigious journals like the NEJM, Lancet, Circulation, JACC, Nature, and JCI and he is currently an Associate Editor of the European Heart Journal. Dr Verma is an active contributor to Canadian clinical practice guidelines and recently co-authored the recommendations for atrial fibrillation, antiplatelet therapy, heart failure and diabetes; he was a member of the 2018 AATS consensus guidelines committee on bicuspid aortic valve-related aortopathy. Dr Verma has served in various capacities on the American Heart Association Council on Cardiovascular Surgery and Anesthesia since 2008. Dr Verma has leadership roles on seven global heart failure trials in diabetes – DAPA-HF, DELIVER, DETERMINE-A, DETERMINE-B, EMPEROR-Preserved, EMPEROR-Reduced and SOLOIST-WHF. He is also involved in the DAPA ACT HF-TIMI 68, FINEARTS-HF, STEP HFpEF, VESALIUS-CV, DARE-19, SELECT and CLEAR SYNERGY trials. He founded and oversees the CardioLink platform at St Michael's Hospital that is conducting cardiometabolic and surgically oriented RCTs and translational studies. Dr Verma leads a dynamic pre-clinical and translational research team that leverages pre-clinical disease models and clinical trial-derived data to identify novel mediators of cardiovascular and cardiometabolic disease as well as answer timely and relevant healthcare questions. His research has yielded two United States patents and is supported by several national peer-reviewed grants. Bobby YanagawaBobby YanagawaBobby Yanagawa is a surgeon in the Division of Cardiac Surgery, St Michael's Hospital, Canada. He is an Assistant Professor and Program Director, Division of Cardiac Surgery at the University of Toronto, Canada. Dr Yanagawa obtained his BSc and PhD from the University of British Columbia, Canada, and his MD degree and Cardiac Surgery Residency from the University of Toronto. He has completed research fellowships at the University of Wales College of Medicine and at St Michael's Hospital, Toronto, Canada. He completed a clinical fellowship at Mount Sinai Hospital, New York, USA. His clinical and research interests are in surgical revascularization and valvular surgery. Dr Yanagawa has published over 100 peer reviewed papers, 50 reviews and 15 book chapters. He has published in Nature Communications, Nature Medicine, Circulation, Journal of Thoracic and Cardiovascular Surgery and Annals of Thoracic Surgery. He was the AATS 13th Annual C. Walton Lillehei Award winner in 2010.

How epigenomics broke the mold: an interview with Peter WLaird.

In this interview, Professor Peter WLaird speaks with Storm Johnson, Commissioning Editor for Epigenomics, on his work to date in the field of cancer epigenetics. DrPeter WLaird is a Professor at Van Andel Institute (VAI) in Grand Rapids, Michigan. He earned his B.S. and M.S., Cum Laude, from the University of Leiden, The Netherlands. He trained for his PhDwith DrPiet Borst, TheNetherlands Cancer Institute, and as a postdoc with DrAnton Berns, TheNetherlands Cancer Institute, and with DrRudolf Jaenisch, at the Whitehead Institute for Biomedical Research in Cambridge, MA, USA. He joined the faculty at the University of Southern California in 1996, where he served as the Founding Director of the USC Epigenome Center and alsoas theLeader of the Epigenetics and Regulation Program of the Norris Comprehensive Cancer Center. In 2014, he relocated to VAI to join DrPeter Jones in building an internationally acclaimed research center focused on Epigenetics. DrLaird published the first demonstration of thecausal role for DNA methylation in oncogenesis (Cell, 1995) [1]. He served as thePrincipal Investigator for all DNA methylation data production for the Cancer Genome Atlas (TCGA) and led many TCGA analysis efforts. He has been awarded 10 patents related to DNA methylation technology by the United States Patent and Trademark Office, one of which is the basis for the first USFDA-approved blood-based DNA methylation assay for cancer (Epi proColon). His research findings include the report of a close link between DNA methylation and BRAF mutation in colorectal cancer (Nature Genetics, 2006) [2], the discovery that embryonic stem cell polycomb repressor targets are predisposed to abnormal DNA methylation in cancer (Nature Genetics, 2007) [3], the identification of a novel epigenetic subtype of glioma (G-CIMP), tightly associated with IDH1 mutation (Cancer Cell, 2010) [4], and the connection between nuclear architecture, late replication, and domains of epigenetic instability (Nature Genetics, 2011) [5], later showing a link with mitotic cell division, thus providing a mechanistic explanation for the loss of DNA methylation in aging and cancer first described four decades ago (Nature Genetics, 2018) [6].

Social capital as the main driver of organizationally valuable innovation

PurposeThrough a juxtaposition of social capital with two other forms of intellectual capital – human capital and organizational capital – the author proposes and tests a framework that sets social capital apart as the main driver of innovations that contribute subsequent technical value to the innovating organization.Design/methodology/approachThis study uses data collected from the United States Patent and Trademark Office (USPTO) for measurement of the key variables. Specifically, the analysis includes all 117 innovations patented under the thermal inkjet printing subclass that were issued in the twenty years following the establishment of that specific subclass in 1980. The author also collected additional data on the individuals and organizations listed on each patent.FindingsThe results of the analysis show that all intellectual capital is not the same and that social capital resulting from collaborative relationships among inventors has significantly more positive influence on the retained technical value of an innovation than organizational or human capital.Practical implicationsRather than tout the primacy of individual intelligence to the generation of valuable innovation, this research suggests that it is preferable to bring together a group of inventors with narrow individual scientific expertise who instead rely on broad collaboration networks as a flexible source of diverse knowledge.Originality/valueThis research addresses an area of innovation research that has not been adequately explored – how do different forms of intellectual capital affect the value the resulting innovation has to the innovating organization?

Can firms avoid tough patent examiners through examiner‐shopping? Strategic timing of citations in USPTO patent applications

AbstractResearch summaryWe claim that, because patent citations influence examiner selection, firms disclose citations strategically to influence which examiner is assigned to their application (“examiner‐shopping”). Specifically, firms are more likely to cite patents reviewed by “lenient” examiners in their original information disclosure statement (IDS) (sent before the examiner has been selected), and delay citations to patents reviewed by “tough” examiners to subsequent IDS (sent once the examiner has been selected). We propose this strategy will be implemented by those firms who benefit the most (firms that face patent thickets and are developing high strategic‐stakes technologies) but only when the costs are low (when firms face a low probability of patent litigation). We find support to our theory in a sample of 9,763 United States patent and trademark office (USPTO) patent applications during 2000 to 2006.Managerial summaryWe find that firms facing patent thickets and developing high strategic stakes technologies try to get more “lenient” examiners to increase the probability of patent approval. The cost of this strategy is that “lenient” examiners usually grant weaker patents that are more likely to be litigated and invalidated. Firms overcome this by using “examiner‐shopping” mainly in fields where litigation is relatively infrequent. This behavior has relevant implications: fields where property rights are rarely challenged tend to become “denser” and populated by weaker patents. Our study's discussion of the limitations within the United States patent and trademark office (USPTO) that seem to provide the opportunity to implement “examiner‐shopping” strategies provides a path to address this from a policy standpoint.

Establish a patent risk prediction model for emerging technologies using deep learning and data augmentation

Technology patents are considered the source and bedrock of emerging technologies. Patents create value in any enterprise. However, obtaining patents is time consuming, expensive, and risky; especially if the patent application is rejected. The development of new patents requires extensive costs and resources, but sometimes they may be similar to other patents once the technology is fully developed. They might lack relevant patentable features and as a result, fail to pass the patent examination, resulting in investment losses. Patent infringement is also an especially important topic for reducing the risk of legal damages of patent holders, applicants, and manufacturers. Patent examinations have so far been performed manually. Due to manpower and time limitations, the examination time is exceedingly long and inefficient. Current patent similarity comparison research, and the classification algorithms of text mining are most commonly employed to provide analyses of the possibility of examination approval, but there is insufficient discussion about the possibility of infringement. However, if a new technology or innovation can be accurately determined in advance whether it likely to pass or fail (and why), or is at risk of patent infringement, losses can be mitigated.This research attempts to identify the issues involved in evaluating patent applications and infringement risks from existing patent databases. For each patent application, this research uses Convolutional Neural Networks, CNN + Long Short Term Memory Network, LSTM, prediction model, and the United States Patent and Trademark Office (USPTO) public utility patent application and reviews results based on keyword search. Then, data augmentation is utilized before performing model training; 10% of the approved and rejected applications are randomly selected as test cases, with the remaining 90% of the cases used to train the prediction model of this research in order to determine a model that can predict patent infringement and examination outcomes. Experimental results of the model in this study predicts that the accuracy of each classification is at least 87.7%, and can be used to find the classification of the reason for a rejection of a patent application failure.