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@article{Qi2025,

title = {Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait},

author = {Wenhao Qi and Shiying Shen and Chaoqun dong and Mengjiao Zhao and Shuaiqi Zang and Xiaohong Zhu and Jiaqi Li and Bin Wang and Yankai Shi and Yongze Dong and Huajuan Shen and Junling Kang and Xiaodong Lu and Guowei Jiang and Jingsong Du and Eryi Shu and Qingbo Zhou and Jinghua Wang and Shihua Cao},

url = {https://www.jmir.org/2025/1/e71560/

https://www.jmir.org/2025/1/e71560/PDF},

doi = {10.2196/71560},

year  = {2025},

date = {2025-05-20},

journal = {Journal of Medical Internet Research},

volume = {27},

abstract = {Background: With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore the current research trends and key areas of focus.



Objective: This study aimed to comprehensively evaluate the current status, hot spots, and future trends of global PD biomarker research, and provide a systematic review of deep learning models for freezing of gait (FOG) digital biomarkers.



Methods: This study used bibliometric analysis based on the Web of Science Core Collection database to conduct a comprehensive analysis of the multidimensional landscape of Parkinson digital biomarkers. After identifying research hot spots, the study also followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for a scoping review of deep learning models for FOG from 5 databases: Web of Science, PubMed, IEEE Xplore, Embase, and Google Scholar.



Results: A total of 750 studies were included in the bibliometric analysis, and 40 studies were included in the scoping review. The analysis revealed a growing number of related publications, with 3700 researchers contributing. Neurology had the highest average annual participation rate (12.46/19, 66%). The United States contributed the most research (192/1171, 16.4%), with 210 participating institutions, which was the highest among all countries. In the study of deep learning models for FOG, the average accuracy of the models was 0.92, sensitivity was 0.88, specificity was 0.90, and area under the curve was 0.91. In addition, 31 (78%) studies indicated that the best models were primarily convolutional neural networks or convolutional neural networks–based architectures.



Conclusions: Research on digital biomarkers for PD is currently at a stable stage of development, with widespread global interest from countries, institutions, and researchers. However, challenges remain, including insufficient interdisciplinary and interinstitutional collaboration, as well as a lack of corporate funding for related projects. Current research trends primarily focus on motor-related studies, particularly FOG monitoring. However, deep learning models for FOG still lack external validation and standardized performance reporting. Future research will likely progress toward deeper applications of artificial intelligence, enhanced interinstitutional collaboration, comprehensive analysis of different data types, and the exploration of digital biomarkers for a broader range of Parkinson symptoms.},

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}

@article{Khan2025,

title = {Frailty after Covid: tracing emergent shifts through heterogenous network mapping},

author = {Salman Khan and Tiago Moreira},

url = {https://link.springer.com/article/10.1057/s41285-025-00216-x

https://link.springer.com/content/pdf/10.1057/s41285-025-00216-x.pdf},

doi = {/10.1057/s41285-025-00216-x},

year  = {2025},

date = {2025-03-28},

journal = {Social Theory & Health},

volume = {23},

issue = {1},

edition = {Paul Higgs; Ruth Graham},

abstract = {Taking as a point of departure the role that the category of frailty increasingly plays in the classification, sorting and management of ageing populations in contemporary societies, this paper examines how the onset of Covid-19—as a disease posing the most risk to older adults—affected scientific knowledge production on frailty. Drawing on a theoretically driven network mapping of scientific literature on frailty before and after the pandemic, the paper traces emergent shifts in the evolution of two key discourses of frailty, namely that of the accumulation of deficits and the phenotype, respectively. Our analysis identifies an increased enrolment of frailty as a clinical, prognostic category post-Covid, underpinned by the deficit accumulation model and its key instrument, the frailty index. In parallel, we observe the continuation of laboratory and experimental research on frailty, as aligned with the phenotype approach. We note that in comparison to before Covid, this shift seems to be taking place across a more diversified scientific terrain, with the field of geriatrics playing a central, mediating role between distinct-yet-relational articulations of frailty—those tied to the clinic on one end, and the lab on the other.},

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tppubtype = {article}

}

@article{Zhao2021,

title = {Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles},

author = {Yi Zhao and Lifan Liu and Chengzhi Zhang},

doi = {https://doi.org/10.1016/j.techfore.2021.121344},

year  = {2021},

date = {2021-11-08},

urldate = {2021-11-08},

journal = {Technological Forecasting and Social Change},

volume = {121344},

abstract = {The outbreak of coronavirus disease 2019 (COVID-19) has had a significant repercussion on the health, economy, politics and environment, making coronavirus-related issues more complicated and difficult to adequately address by relying on a single field. Interdisciplinary research can provide an effective solution to complex issues in the related field of coronavirus. However, whether coronavirus-related research becomes more interdisciplinary still needs corroboration. In this study, we investigate interdisciplinary status of the coronavirus-related fields via the COVID-19 Open Research Dataset (CORD-19). To this end, we calculate bibliometric indicators of interdisciplinarity and apply a co-occurrence analysis method. The results show that co-occurrence relationships between cited disciplines have evolved dynamically over time. The two types of co-occurrence relationships, Immunology and Microbiology & Medicine and Chemical Engineering & Chemistry, last for a long time in this field during 1990–2020. Moreover, the number of disciplines cited by coronavirus-related research increases, whereas the distribution of disciplines is uneven, and this field tends to focus on several dominant disciplines such as Medicine, Immunology and Microbiology, Biochemistry, Genetics and Molecular Biology. We also measure the disciplinary diversity of COVID-19 related papers published from January to December 2020; the disciplinary variety shows an upward trend, while the degree of disciplinary balance shows a downward trend. Meanwhile, the comprehensive index 2Ds demonstrates that the degree of interdisciplinarity in coronavirus field decreases between 1990 and 2019, but it increases in 2020. The results help to map the interdisciplinarity of coronavirus-related research, gaining insight into the degree and history of interdisciplinary cooperation.},

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}

@article{Louvel2020,

title = {What’s in a name? The three genealogies of the social insocial epigenetics},

author = {Séverine Louvel},

editor = {SAGE Publications},

doi = {https://doi.org/10.1177/0539018419897001},

year  = {2020},

date = {2020-01-22},

urldate = {2020-01-22},

journal = {Social Science Information},

abstract = {Social  epigenetics  – the  study  of  the  epigenetic  mechanisms  through  which  social  environments  become biologically embodied –   epitomizes recent claims that the boundaries between the natural and the social sciences should be reduced. Relying on a bibliometric study and on a qualitative analysis of publications  in  social  epigenetics,  this   paper   investigates   how   this  research  area defines   and operationalizes  the social dimensions that may have an impact on health status and disease risk. The paper  also  addresses  how  the  social  sciences  engage  with  social  epigenetics.  First,  the  paper  traces  social epigenetics back to five epistemic backgrounds –   two in animal research (on social defeat and early-life  adversity)  and  three  in  human  studies  (on  trauma,  early-life  nutrition  and  social  adversity  over the life-course). Second, it outlines the quest for epigenetic markers of social environments, and the associated expectations and controversies. Third, it analyses the three modes of engagement of the social  sciences  with  human  studies  in  social  epigenetics:  rejection  (social  epigenetics  trapped  in  the  quest  for  a  ‘social  brain’);  warning  and  call  for  responsibility  (social  epigenetics  has  shifted  from socioeconomic   contexts   to   individual   behaviors);   and   support   and   active   contribution   (social   epigenetics may strengthen  social  studies  of  health).  This  paper  argues  that  recent  developments  in  social  epigenetics  could  strengthen  this  third  mode  of  engagement  and  expand  the  scope  of  interdisciplinary collaboration between the natural and the social sciences.},

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pubstate = {published},

tppubtype = {article}

}

@article{Shen2019,

title = {Detecting the Interdisciplinary Nature and Topic Hotspots of Robotics in Surgery: Social Network Analysis and Bibliometric Study},

author = {Lining Shen and Shimin Wang and Wei Dai and Zhiguo Zhang},

doi = {https://doi.org/10.2196/12625},

year  = {2019},

date = {2019-03-19},

urldate = {2019-03-19},

journal = {Journal of Medical Internet Research},

volume = {21},

number = {3},

abstract = {Background: With the widespread application of a robot to surgery, growing literature related to robotics in surgery (RS) documents widespread concerns from scientific researchers worldwide. Although such application is helpful to considerably improve the accuracy of surgery, we still lack the understanding of the multidiscipline-crossing status and topic distribution related to RS. Objective: The aim of this study was to detect the interdisciplinary nature and topic hotspots on RS by analyzing the current publication outputs related to RS. Methods: The authors collected publications related to RS in the last 21 years, indexed by the Web of Science Core Collection. Various bibliometric methods and tools were used, including literature distribution analysis at the country and institution level and interdisciplinary collaboration analysis in the different periods of time. Co-word analysis was performed based on the keywords with high frequency. The temporal visualization bar presented the evolution of topics over time. Results: A total of 7732 bibliographic records related to RS were identified. The United States plays a leading role in the publication output related to RS, followed by Italy and Germany. It should be noted that the Yonsei University in South Korea published the highest number of RS-related publications. Furthermore, the interdisciplinary collaboration is uneven; the number of disciplines involved in each paper dropped from the initial 1.60 to the current 1.31. Surgery; Engineering; Radiology, Nuclear Medicine, and Medical Imaging; and Neurosciences and Neurology are the 4 core disciplines in the field of RS, all of which have extensive cooperation with other disciplines. The distribution of topic hotspots is in imbalanced status, which can be categorized into 7 clusters. Moreover, 3 areas about the evolution of topic were identified, namely (1) the exploration of techniques that make RS implemented, (2) rapid development of robotic systems and related applications in surgery, and (3) application of a robot to excision of tissues or organs targeted at various specific diseases. Conclusions: This study provided important insights into the interdisciplinary nature related to RS, which indicates that the researchers with different disciplinary backgrounds should strengthen cooperation to publish a high-quality output. The research topic hotspots related to RS are relatively scattered, which has begun to turn to the application of RS targeted at specific diseases. Our study is helpful to provide a potential guide to the direction of the field of RS for future research in the field of RS.},

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pubstate = {published},

tppubtype = {article}

}

@article{weisz2017mapping,

title = {Mapping Global Health: A network analysis of a heterogeneous publication domain},

author = {George Weisz and Alberto Cambrosio and Jean-Philippe Cointet},

url = {https://doi.org/10.1057/s41292-017-0053-4},

doi = {10.1057/s41292-017-0053-4},

year  = {2017},

date = {2017-01-01},

urldate = {2017-01-01},

journal = {BioSocieties},

volume = {12},

number = {4},

pages = {520-542},

publisher = {Springer},

abstract = {This paper examines one of the most visible but oddly neglected aspects of the rapidly expanding Global Health (GH) enterprise: its vast literature. Basing our data on the PubMed MeSH term “World Health” (changed to “Global Health” in 2015) and utilizing the citation and funding metadata provided by Web of Science, we analyze nearly 20,000 articles using the software platform CorTexT for the automatic processing of large text corpora. We perform several types of scientometric network analyses, and provide maps displaying inter-citations among journals publishing GH articles, co-authorship among the 292 authors who published 12 or more papers, co-citation analysis of works (articles, books, and reports) cited at least 30 times by the papers in our database, and funding sources since 2008. The maps display the social, cognitive, and funding substructure of the GH publication field. We suggest that this somewhat fragmented and fuzzy domain is held together by (1) a core group of authors who have for some time been co-authoring numerous papers and reports with one another; (2) several central journals, most notably the Lancet, addressing wider audiences and transcending the narrow specialization characteristic of scientific and biomedical fields; and (3) a growing body of large-data metrics, most prominently the Global Burden of Disease, which has become a rhetorical resource for numerous groups with different agendas.},

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}