Search (2 results, page 1 of 1)

  • × author_ss:"Leydesdorff, L."
  • × author_ss:"Rafols, I."
  • × author_ss:"Rotolo, D."
  1. Leydesdorff, L.; Rotolo, D.; Rafols, I.: Bibliometric perspectives on medical innovation using the medical subject headings of PubMed (2012) 0.00 
    0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 494) [ClassicSimilarity], result of:
          0.00994303 = score(doc=494,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 494, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=494)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the MEDLINE database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the MEDLINE database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the MEDLINE database on one hand, and the Science Citation Index and Scopus (containing citation information) on the other.
    Type
    a
  2. Rotolo, D.; Rafols, I.; Hopkins, M.M.; Leydesdorff, L.: Strategic intelligence on emerging technologies : scientometric overlay mapping (2017) 0.00 
    0.001757696 = product of:
  0.003515392 = sum of:
    0.003515392 = product of:
      0.007030784 = sum of:
        0.007030784 = weight(_text_:a in 3322) [ClassicSimilarity], result of:
          0.007030784 = score(doc=3322,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.13239266 = fieldWeight in 3322, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3322)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    This paper examines the use of scientometric overlay mapping as a tool of "strategic intelligence" to aid the governing of emerging technologies. We develop an integrative synthesis of different overlay mapping techniques and associated perspectives on technological emergence across geographical, social, and cognitive spaces. To do so, we longitudinally analyze (with publication and patent data) three case studies of emerging technologies in the medical domain. These are RNA interference (RNAi), human papillomavirus (HPV) testing technologies for cervical cancer, and thiopurine methyltransferase (TPMT) genetic testing. Given the flexibility (i.e., adaptability to different sources of data) and granularity (i.e., applicability across multiple levels of data aggregation) of overlay mapping techniques, we argue that these techniques can favor the integration and comparison of results from different contexts and cases, thus potentially functioning as a platform for "distributed" strategic intelligence for analysts and decision makers.
    Type
    a