Skip to main content
SpringerLink
Log in

Visualizing the structure and the evolving of digital medicine: a scientometrics review

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

This article aims to analyze and visualize the structure and the emerging trend of digital medicine, a new medical pattern of twenty-first century. Our study objectively explores the document co-citation clusters of 6060 bibliographic records to identify the origin of digital medicine and the hot research specialty of domain. Pivotal point articles, prominent authors, active disciplines and institution have been identified by network analysis theory. CiteSpace was used to visualize the perspective of digital medicine domain. As an interdiscipline which integrated computer science, information engineering with medicine, digital medicine originally and mainly on digital medical imaging technology research for accuracy and speedy clinical diagnosis and therapy. Of 6060 relevant records reviewed, 1719 (28 %) are on radiology, 902 (15 %) are on engineering, 539 (9 %) are on computer science. The largest co-citation cluster is on digital tomosynthesis. The earliest cluster is on medical imaging segmentation and registration. Post-processing imaging technology, detector, phase contrast, reversible watermarking, input, model 3D reconstruct, real-time dynamic imaging, dosimetry have been the hot research topics. The recently cluster is on internet health information. Harvard University of USA is the prominent institution. The coverage of digital medicine research is widely from clinic to laboratory. Recent year, domain research front is thematically on teleradiology, telemedicine and hospital information management system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

References

  • Acciavatti, R. J., & Maidment, A. D. A. (2010). A comparative analysis of OTF, NPS, and DQE in energy integrating and photon counting digital X-ray detectors. Medical Physics, 37(12), 6480–6495.

    Article  Google Scholar 

  • Adams, C. M., & Wilson, T. D. (2011). Virtual cerebral ventricular system: an MR-based three-dimensional computer model. Anatomical Sciences Education, 4(6), 340–347.

    Article  Google Scholar 

  • Armfield, N. R., Edirippulige, S., & Caffery, L. J. (2014). Telemedicine-A bibliometric and content analysis of 17,932 publication records. Internatioal Journal of Medical Informatics, 83(10), 715–725.

    Article  Google Scholar 

  • Barnes, G. T., Sones, R. A., & Tesic, M. M. (1985). Detector for dual-energy digital radiography. Radiology, 156(2), 537–540.

    Article  Google Scholar 

  • Bibin, L., Anquez, J., & Angelini, E. (2010). Hybrid 3D pregnant woman and fetus modeling from medical imaging for dosimetry studies. International Journal of Computer Assisted Radiology and Surgery, 5(1), 49–56.

    Article  Google Scholar 

  • Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 1, 307–310.

  • Burdett, E., Kasper, F. K., & Mikos, A. G. (2010). Engineering tumors: A tissue engineering perspective in cancer biology. Tissue Engineering Part B-Reviews, 16(3), 351–359.

    Article  Google Scholar 

  • Castelli, E., Tonutti, M., & Arfelli, F. (2011). Mammography with synthrotron radiation: First clinical experience with phase-detection technique. Radiology, 259, 684–694.

  • Chen, C. M. (2004). Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences of the United States of America, 101(suppl. 1), 5303–5310.

    Article  Google Scholar 

  • Chen, C. M. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. JASIST, 57(3), 359–377.

    Article  Google Scholar 

  • Chen, C. M., Chen, Y., & Horowitz, M. (2009). Towards an explanatory and computational theory of scientific discovery. Journal of Informetrics, 3, 191–209.

    Article  Google Scholar 

  • Chen, C. M., Dubin, R., & Kim, M. C. (2014a). Orphan drugs and rare diseases: A scientometric review (2000–2014). Expert Opinion on Orphan Drugs, 2(7), 1–16.

    Article  MATH  Google Scholar 

  • Chen, C. M., Dubin, R., & Kim, M. C. (2014b). Emerging trends and new developments in regenerative medicine: A scientometric update (2000–2014). Expert Opinion on Biological Therapy, 14(9), 1295–1317.

    Article  Google Scholar 

  • Chen, C. M., SanJuan, F. I., & Hou, J. H. (2010). The structure and dynamics of co-citation clusters: A multiple-perspective co-citation analysis. JASIST, 61(7), 1386–1409.

    Article  Google Scholar 

  • Chen, C. M., Song, I. Y., & Yuan, X. J. (2008). The thematic and citation landscape of data and Knowledge engineering (1985–2007). Data & Knowledge Engineering, 67, 234–259.

    Article  Google Scholar 

  • Cheng, F. X., & Zhao, Z. M. (2014). Machine learning-based prediction of drug–drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties. Journal of the American Medical Informatics Association, 21, e278–e286.

    Article  Google Scholar 

  • Chida, K., Morohashi, G., & Fuji, H. (2014). Implementation and evalution of an efficient secure computation system suing ‘R’ for healthcare statistics. Journal of the American Medical Informatics Association, 21, e326–e331.

    Article  Google Scholar 

  • Cong, W., & Wang, G. (2010). Higher-order phase shift reconstruction approach. Medical Physics, 37(10), 5238–5242.

    Article  Google Scholar 

  • Ding, G. X., & Coffey, C. W. (2009). Radiation dose from kilovoltage cone beam computed tomography in an image-guided radiotherapy procedure. International Journal of Radiation Oncology Biology Physics, 73(2), 610–617.

    Article  Google Scholar 

  • Feldkamp, L., Lalush, D., & Kress, J. (1984). Practical cone-beam algorithm. Journal of the Optical Society of America A, 1, 612–619.

    Article  Google Scholar 

  • Fredenberg, E., Danielsson, M., & Stayman, J. W. (2012). Ideal-observer detectability in photon-counting differential phase-contrast imaging using a linear-systems approach. Medical Physics, 39(9), 5317–5335.

    Article  Google Scholar 

  • Frederik, M., Collignon, A., & Vandermeulen, D. (1997). Multimodality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging, 16(2), 187–198.

    Article  Google Scholar 

  • Gallo, L., Minutolo, A., & De Pietro, G. (2010). A user interface for vr-ready 3D medical imaging by off-the-shelf input devices. Computers in Biology and Medicine, 40(3), 350–358.

    Article  Google Scholar 

  • Gøeg, K. R., Chen, R., & Højen, A. R. (2014). Content analysis of physical examination templates in electronic health records using SNOMED CT. International Journal of Medical Informatics, 83, 736–749.

    Article  Google Scholar 

  • Guo, J. S. (2004). Networking development trends of modern medical imaging technology. Image Technology, 4, 3–7.

    Google Scholar 

  • Jayaprakasan, K., Hilwah, N., & Kendall, N. R. (2007). Does 3D ultrasound offer any advantage in the pretreatment assessment of ovarian reserve and prediction of outcome after assisted reproduction treatment? Human Reproduction, 22(7), 1932–1941.

    Article  Google Scholar 

  • Jemal, A., Bray, F., & Center, M. M. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61(2), 69.

  • Jiang, H. J., & Li, D. Q. (2013). Application of PACS system in the practice teaching of medical imaging. China Medical Education Technology, 27(5), 565–567.

    Google Scholar 

  • Jiang, L. C., Wang, Z. Z., & Peng, T. Q. (2015). The divided communities of shared concerns: Mapping the intellectual structure of e-Health research in social science journals. International Journal of Medical Informatics, 84(9), 24–35.

    Article  Google Scholar 

  • Jones, D. S., Cambrosio, A., & Mogoutov, A. (2011). Detection and characterization of translational research in cancer and cardiovascular medicine. Journal of Translational Medcine, 9(1), 1–12.

    Article  Google Scholar 

  • Keedy, A. W., Durack, J. C., & Sandhu, P. (2011). Comparison of traditional methods with 3D computer models in the instruction of hepatobiliary anatomy. Anatomical Sciences Education, 4(2), 84–91.

    Article  Google Scholar 

  • Kim, M. C., Jeong, Y. K., & Song, M. (2014). Investigating the integrated landscape of the intellectual topology of bioinformatics. Scientometrics, 101, 309–335.

    Article  Google Scholar 

  • Klein, S., Staring, M., & Murphy, K. (2009). Elastix: a toolbox for intensity-based medical image registration. IEEE Transactions on Medical Imaging, 29(1), 196–205.

    Article  Google Scholar 

  • Kuang, Y. W., Gary, K., & Fang, Z. (2007). Consumers’ perceptions about and use of the internet for personal health records and health information exchange: Analysis of the 2007 health information national trends survey. Journal of Medical Internet Research, 12(4), e73.

    Google Scholar 

  • Lazos, D., & Williamson, J. F. (2010). Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT. Medical Physics, 37(10), 5456–5470.

    Article  Google Scholar 

  • Liu, Y. B. (2014). Digital medicine-A significant leap of medicine domain of 21th century. The Journal of Practical Medicine, 30(2), 172–173.

    Google Scholar 

  • Low, D. A., Harms, W. B., & Mutic, S. (1998). A technique for the quantitative evaluation of dose distributions. Medical Physics, 25, 656.

  • Low, D., Moran, J. M., & Dempsey, J. F. (2011). Dosimetry tools and techniques for imrt. Medical Physics, 38(3), 1313–1368.

    Article  Google Scholar 

  • Low, D. A., Nystrom, M., & Kalinin, E. (2003). A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. Medical Physics, 30(6), 1254–1263.

    Article  Google Scholar 

  • Lu, Q. P. (2013). A transformation from digital medicine to translational medicine: what roles should clinical doctors play in different phases (T1, T2 and T3) of digital medicine. Chinese Journal of Practical Surgery, 33(1), 21–24.

    Google Scholar 

  • Lv, T. (2010). Research and application of digital human. Journal of Clinical Rehabilitative Tissue Engineering Research, 14(48), 8041–8045.

    Google Scholar 

  • Maes, F., Collignon, A., & Vandermeulen, D. (1997). Multimodality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging, 16(2), 187–198.

  • Memon, N. A., Khan, A., & Gilani, S. A. M. (2011). Reversible watermarking method based on adaptive thresholding and companding technique. International Journal of Computer Mathematics, 88(8), 1573–1594.

    Article  MathSciNet  MATH  Google Scholar 

  • Miller, J. S., Stevens, K. R., & Yang, M. T. (2012). Rapid casting of patterned vascular networks for perfusable engineered three-dimensional tissues. Nature Materials, 11, 768.

  • Ming, C. (2010). Model order selection in reversible image watermarking. IEEE Journal of Selected Topics in Signal Processing, 4(3), 592–604.

    Article  Google Scholar 

  • Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, Cybernetics, 9(1), 62–66.

    Article  MathSciNet  Google Scholar 

  • Park, S., Jennings, R. J., & Liu, H. (2010a). A statistical, task-based evaluation method for three-dimensional X-ray breast imaging systems using variable-background phantoms. Medical Physics, 37(12), 6253–6270.

    Article  Google Scholar 

  • Park, C. H., Rios, H. F., & Jin, Q. (2010b). Biomimetic hybrid scaffolds for engineering human tooth–ligament interfaces. Biomaterials, 31(23), 5945–5952.

    Article  Google Scholar 

  • Persson, O. (1994). The intellectual base and research fronts of JASIS 1986–1990. JASIS, 45(1), 31–38.

    Article  Google Scholar 

  • Peters, J., Ecabert, O., & Meyer, C. (2010). Optimizing boundary detection via simulated search with applications to multi-modal heart segmentation. Medical Image Analysis, 14(1), 70–84.

    Article  Google Scholar 

  • Pisano, E., Gatsonis, C., & Hendrick, R. E. (2005). Diagnostic performance of digital versus film mammography for breast-cancer screening. New England Journal of Medicine, 353(17), 1773–1783.

    Article  Google Scholar 

  • Price, D. D. (1965). Networks of scientific papers. Science, 149(3683), 510–515.

    Article  Google Scholar 

  • Qin, W. C. (2007). The status and development of medical imaging technology. Chinese Journal of Radiology, 41(2), 113–114.

    Google Scholar 

  • Reiser, I., & Nishikawa, R. M. (2010). Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noise. Medical Physics, 37(4), 1591–1600.

    Article  Google Scholar 

  • Ribitsch, I., Burk, J., & Delling, U. (2010). Basic science and clinical application of stem cells in veterinary medicine. Biotechnology, 123, 219–263.

    Google Scholar 

  • Rorissa, A., & Yuan, X. J. (2012). Visualizing and mapping the intellectual structure of information retrieval. Information Processing & Managgment, 48, 120–135.

    Article  Google Scholar 

  • Salama, S., Arbo, E., & Lamazou, F. (2010). Reproducibility and reliability of automated volumetric measurement of single preovulatory follicles using SonoAVC. Fertility and Sterility, 93(6), 2069–2073.

    Article  Google Scholar 

  • Salomon, A., Goedicke, A., & Aach, T. (2010). Attenuation corrected cardiac spect imaging using simultaneous reconstruction and a priori information. IEEE Transactions of Nuclear Science, 58(2), 527–536.

    Article  Google Scholar 

  • Sarkar, U., Karter, A. J., & Liu, J. Y. (2011). Social disparities in internet patient portal use in diabetes: Evidence that the digital divide extends beyond access. Journal of the American Medical Informatics Association, 18(3), 318–321.

    Article  Google Scholar 

  • Shams, R., Sadeghi, P., & Kennedy, R. (2009). Parallel computation of mutual information on the gpu with application to real-time registration of 3D medical images. Computer Methods and Programs in Biomedicine, 99(2), 133–146.

    Article  Google Scholar 

  • Small, H. (1981). The relationship of information science to the social sciences: A co-citation analysis. Information Processing and Management, 17(1), 39–50.

    Article  Google Scholar 

  • Small, H., & Griffith, B. C. (1974). The structure of scientific literature I: Identifying and graphing specialties. Science Studies, 4(1), 17–40.

    Article  Google Scholar 

  • Snigirev, A., Snigireva, I. I., & Kohn, V. (1996). On the possibilities of X-ray phase contrast microimaging by coherent high-energy synchrotron radiation. Review of Scientific Instruments, 66(12), 5486–5492.

    Article  Google Scholar 

  • Snigirev, A., Snigireva, I., Kohn, V., Kuznetsov, S., & Schelokov, I. (1995). On the possibilities of X-ray phase contrast microimaging by coherent high-energy synchrotron radiation. Review of Scientific Instruments, 66(12), 5486–5492.

    Article  Google Scholar 

  • Tang, L., & Gu, D. Y. (2012). What does the digital medicine bring us. Science, 64(4), 4–7.

    Google Scholar 

  • Thomas, A., Newton, J. R., & Adamovics, J. (2011). Commissioning and benchmarking a 3D dosimetry system for clinical use. Medical Physics, 38(8), 4846–4857.

    Article  Google Scholar 

  • Wang, J. (2002). Rapid development of medical imaging technology. Image Technology, 2, 37–40.

    Google Scholar 

  • Wang, J., Mao, W. H., & Solberg, T. (2010). Scatter correction for cone-beam computed tomography using moving blocker strips: A preliminary study. Medical Physics, 37(11), 5792–5800.

    Article  Google Scholar 

  • Winnink, J. J., & Tijssen, R. J. W. (2014). R & D dynamics and scientific breakthroughs in HIV/AIDS drugs development: The case of Integrase Inhibitors. Scientometrics, 101, 1–16.

    Article  Google Scholar 

  • Xie, N. Z. (2002). New development of national and international digital medicine technology. Journal of Modern Clinical Medical Bioengineering, 8(5), 316–317.

    Google Scholar 

  • Yao, Q., Chen, K., & Yao, L. (2014a). Scientometric trends and knowledge maps of global health systems research. Health Research Policy and Systems, 26(12), 1–20.

    Google Scholar 

  • Yao, Q., Lyu, P. H., & Yang, L. P. (2014b). Current performance and future trends in health care sciences and services research. Scientometrics, 101, 751–779.

    Article  Google Scholar 

  • Ye, Y., Tsui, F. C., & Wagner, M. (2014). Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers. Journal of the American Medical Informatics Association, 21, 815–823.

    Article  Google Scholar 

  • Yu, A. M., & Fu, Y. (2010). Analysis of the progress of digital medical imaging technology. China Medical Devices, 25(12), 38–41.

    Google Scholar 

  • Zhong, S. Z. (2003a). Scientific significance and prospective application of digitized virtual human. Journal of First Military Medical University, 23(3), 193–195.

    Google Scholar 

  • Zhong, S. Z. (2003b). Actualities and prospects of research on digitized virtual human. Medical Journal of Chinese People’s Liberation Army, 28(5), 385–388.

    Google Scholar 

  • Zhong, S. Z. (2009). From digital human to digital medicine. Journal of Medical Research, 38(8), 1–2.

    Google Scholar 

  • Zudilova-Seinstra, E. V., de Koning, P. J. H., & Suinesiaputra, A. (2010). Evaluation of 2D and 3D glove input applied to medical image analysis. International Journal of Human–Computer Studies, 68(6), 355–369.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Library, Nankai University, No. 94 Weijin Road, Nankai District, Tianjin, China

    Yuqing Fang

Authors
  1. Yuqing Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuqing Fang.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 98 kb)

Appendix

Appendix

See Tables 1, 2, 3 and 4.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, Y. Visualizing the structure and the evolving of digital medicine: a scientometrics review. Scientometrics 105, 5–21 (2015). https://doi.org/10.1007/s11192-015-1696-1

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-015-1696-1

Keywords

Search

Navigation