Patent bibliometrics in spinal deformity: the first bibliometric analysis of spinal deformity's technological literature

PURPOSE

Bibliometric analyses have gained popularity for studying scientific literature, but their application to evaluate technological literature (patents) remains unexplored. We conducted a bibliometric analysis on the top 100 most-cited patents in scoliosis surgery.

METHODS

Multiple databases were queried using The Lens to identify the top 100 scoliosis surgery patents, which were selected based on forward patent citations. These patents were then categorized into 8 groups based on technological descriptors and assessed based on various factors including earliest priority date, year issued, and expiration status.

RESULTS

The top 100 most-cited patents included technology underlying anterolateral tethering and distraction systems (n = 11), posterior tethering and distraction systems (n = 23), posterior segmental bone anchor and rod engagement systems (n = 29), interbody devices (n = 10), biological and electrophysiological agents for scoliosis treatment and/or improved arthrodesis (n = 8), intraoperative arthroplasty devices (n = 5), orthotic devices (n = 12), and implantable devices for non-invasive, postoperative alterations of skeletal alignment (n = 2). Seventy-five patents were expired, 21 are still active, and 4 were listed as inactive. The late 1970s and early 2000s saw increased numbers of patent filings. Demonstrated trends showed no meaningful correlation between patent rank and earliest priority date (linear trendline y = 0.2648x - 477.27; R2 = 0.0114), while a very strong correlation was found between patent rank and citations per year (power trendline y = 118.82x--0.83; R2 = 0.8983).

CONCLUSION

Patent bibliometric analyses in the field of spinal deformity surgery provide a means to assess past advancements, better understand what it takes to make a difference in the field, and to potentially facilitate the development of innovative technologies in the future. The method described is a reliable and reproducible technique for evaluating technological literature in our field.

LEVEL OF EVIDENCE: 3

The 100 most cited articles on trachoma: a bibliometric analysis

OBJECTIVE

Trachoma is the cause of blindness or visual impairment in 1.9 million people. Few bibliometric studies have been carried out, but none explore the characteristics of the 100 most cited articles on trachoma.

METHODS

A keyword-based search without time restriction was performed in September 2022 using the Scopus database. Search keywords include the following: "trachoma; trachome; tracoma; trachomatis." Two authors independently screened the literature and extracted data. The search result was obtained to classify the 100 articles according to their number of citations.

RESULTS

The Top 100 articles were published between 1957 and 2015 with a total of 11,102 citations (range 56-689). The country with the most significant contribution was the USA (n = 56). The Lancet was the most active journal (n = 15). Bailey RL was the author with the highest number of publications (n = 30). The Edna McConnell Clark Foundation (n = 26) was the most prominent funding entity. The type of original article was the most published (n = 83), in addition, the most frequent thematic area was prevention (n = 33). The most popular keywords were trachoma (n = 93), chlamydia trachomatis (n = 55), and azithromycin (n = 34).

CONCLUSIONS

The study provides new insight into trachoma research, information that may help healthcare providers, researchers, and stakeholders better understand trends and influential contributions. It highlights under-researched areas that could be the basis for future research.

Review: Patent Bibliometrics in Cranial Neurosurgery: The First Bibliometric Analysis of Neurosurgery's Technological Literature

BACKGROUND

Bibliometric analyses of the scientific literature have grown increasingly popular in the past few decades. However, patent bibliometric studies, evaluation of technological literature, have not yet been applied in neurosurgery.

OBJECTIVE

To perform a pilot patent bibliometric analysis of the top 100 most cited patents in cranial neurosurgery.

METHODS

The Lens was used to query multiple databases, to select the top 100 cranial neurosurgical patents based upon forward patent citations. These were organized into 9 categories based on technological descriptors and were evaluated based on the earliest priority date, year issued, and expiration status, among others.

RESULTS

The top 100 most cited patents included technology underlying 3D navigation (n = 31), pharmacology and implants (n = 20), vascular occlusion (n = 5), craniotomy closure (n = 9), focal lesioning and tissue resection (n = 8), brain and systemic cooling (n = 5), neuroendoscopy (n = 8), neuromonitoring and stimulation (6), and technologies improving surgeon performance (n = 8). Ninety-six patents were filed in the United States, 72 were expired, 19 are still active, and 9 were listed as inactive. The highest number of patents was applied for from the mid-1990s to the mid-2000s. Demonstrated trends showed no meaningful correlation between patent rank and earliest priority date (linear trendline y = 0.7107 x -1367.5; R² = 0.0671), while a very strong correlation was found between patent rank and citations per year (power trendline y = 127.93 x -1.094; R² = 0.8579).

CONCLUSIONS

Patent bibliometrics allow evaluation of neurosurgical advancements from the past and enable subsequent development of cutting-edge technology in the future. The described method is a reproducible and reliable technique for evaluating our field's patent literature.

Opinion texts summarization based on texts concepts with multi-objective pruning approach

Considering the huge volume of opinion texts published on various social networks, it is extremely difficult to peruse and use these texts. The automatic creation of summaries can be a significant help for the users of such texts. The current paper employs manifold learning to mitigate the challenges of the complexity and high dimensionality of opinion texts and the K-Means algorithm for clustering. Furthermore, summarization based on the concepts of the texts can improve the performance of the summarization system. The proposed method is unsupervised extractive, and summarization is performed based on the concepts of the texts using the multi-objective pruning approach. The main parameters utilized to perform multi-objective pruning include relevancy, redundancy, and coverage. The simulation results show that the proposed method outperformed the MOOTweetSumm method while providing an improvement of 11% in terms of the ROGUE-1 measure and an improvement of 9% in terms of the ROGUE-L measure.