We present the results of a scientometric analysis of 30 years of IEEE VIS publications between 1990-2020, in which we conducted a multifaceted analysis of interdisciplinary collaboration and gender composition among authors. To this end, we curated BiblioVIS, a bibliometric dataset that contains rich metadata about IEEE VIS publications, including 3032 articles and 6113 authors. One of the main factors differentiating BiblioVIS from similar datasets is the authors' gender and discipline data, which we inferred through iterative rounds of computational and manual processes. Our analysis shows that, by and large, inter-institutional and interdisciplinary collaboration has been steadily growing over the past 30 years. However, interdisciplinary research was mainly between a few fields, including Computer Science, Engineering and Technology, and Medicine and Health disciplines. Our analysis of gender shows steady growth in women's authorship. Despite this growth, the gender distribution is still highly skewed, with men dominating ( ≈ 75%) of this space. Our predictive analysis of gender balance shows that if the current trends continue, gender parity in the visualization field will not be reached before the third quarter of the century ( ≈ 2070). Our primary goal in this work is to call the visualization community's attention to the critical topics of collaboration, diversity, and gender. Our research offers critical insights through the lens of diversity and gender to help accelerate progress towards a more diverse and representative research community.
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http://dx.doi.org/10.1109/TVCG.2022.3158236 | DOI Listing |
Phys Rev Lett
December 2024
CERN, Geneva, Switzerland.
High-energy nuclear collisions create a quark-gluon plasma, whose initial condition and subsequent expansion vary from event to event, impacting the distribution of the eventwise average transverse momentum [P([p_{T}])]. Disentangling the contributions from fluctuations in the nuclear overlap size (geometrical component) and other sources at a fixed size (intrinsic component) remains a challenge. This problem is addressed by measuring the mean, variance, and skewness of P([p_{T}]) in ^{208}Pb+^{208}Pb and ^{129}Xe+^{129}Xe collisions at sqrt[s_{NN}]=5.
View Article and Find Full Text PDFCancer Biol Med
January 2025
Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Artificial intelligence (AI) is significantly advancing precision medicine, particularly in the fields of immunogenomics, radiomics, and pathomics. In immunogenomics, AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis, thus providing strong support for personalized treatments. In radiomics, AI can analyze high-dimensional features from computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography/computed tomography (PET/CT) images to discover imaging biomarkers associated with tumor heterogeneity, treatment response, and disease progression, thereby enabling non-invasive, real-time assessments for personalized therapy.
View Article and Find Full Text PDFDrug Des Devel Ther
January 2025
Department of Infectious Diseases, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, People's Republic of China.
In recent years, the incidence of fungal infections has been rising annually, especially among immunocompromised populations, posing a significant challenge to public health. Although antifungal medications provide some relief, the escalating problem of resistance sharply curtails their effectiveness, presenting an urgent clinical dilemma that demands immediate attention. Research has shown that fungal resistance is closely related to quorum sensing (QS), and QS inhibitors (QSIs) are considered an effective solution to this issue.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Faculty of Health Sciences, Department of Rehabilitation Science and Health Technology, OsloMet - Oslo Metropolitan University, Oslo, Norway.
Background: As the population ages, more people live longer with multimorbidity. Older people with multimorbidity face diverse needs and medical conditions, increasing the risk of adverse health outcomes, and often experience fragmented healthcare. Research has called for better ways to reach, understand and care for this group to enhance care continuity.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Oral and Dental Disease Research Center, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran.
Background: Molariform second premolar is a rare dental anomaly where the second premolar resembles a molar in size and shape. This condition is often linked to macrodontia, a rare enlargement of teeth that disrupts dental proportions and can manifest in isolated, relative, or generalized forms. Although mandibular second premolars are more prone to morphological variability, the occurrence of bilateral molariform premolars, induced by a unique form of gemination, is exceptionally uncommon and infrequently documented, thus making this case clinically significant.
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