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The essence of text mining and data mining is that a machine and software are used for content analysis of large digital corpora. The Publishing Research Consortium commissioned a study on content mining of scholarly journal articles with 29 expert interviews and an international survey among publishers. The main results are: (i) content mining developments appear to be accelerating with more applications in more areas; (ii) third‐party demand for content mining is widespread but still at low levels of frequency; (iii) publishers' permissions for content mining are quite liberal, especially for research‐driven mining requests; (iv) half of the publisher respondents undertake mining of their own content; and (v) content mining is on the rise – publishers and third parties both report an increase in planned mining activities. As content mining of journal articles spreads and intensifies, cross‐publisher solutions can better help facilitate content mining. The study investigated the interest and willingness of publishers to support a set of different solutions, from one shared content mining platform to commonly agreed access terms for mining and standardization of mining‐friendly content formats.

BackgroundInverse potential mapping (IPM) noninvasively reconstructs cardiac surface potentials using body surface potentials. This requires a volume conductor model (VCM), usually constructed from computed tomography; however, computed tomography exposes the patient to harmful radiation and lacks information about tissue structure. Magnetic resonance imaging (MRI) is not associated with this limitation and might have advantages for mapping purposes. This feasibility study investigated a magnetic resonance imaging–based IPM approach. In addition, the impact of incorporating the lungs and their particular resistivity values was explored.Methods and ResultsThree volunteers and 8 patients with premature ventricular contractions scheduled for ablation underwent 65‐electrode body surface potential mapping. A VCM was created using magnetic resonance imaging. Cardiac surface potentials were estimated from body surface potentials and used to determine the origin of electrical activation. The IPM‐defined origin of sinus rhythm corresponded well with the anatomic position of the sinus node, as described in the literature. In patients, the IPM‐derived premature ventricular contraction focus was 3‐dimensionally located within 8.3±2.7 mm of the invasively determined focus using electroanatomic mapping. The impact of lungs on the IPM was investigated using homogeneous and inhomogeneous VCMs. The inhomogeneous VCM, incorporating lung‐specific conductivity, provided more accurate results compared with the homogeneous VCM (8.3±2.7 and 10.3±3.1 mm, respectively; P=0.043). The interobserver agreement was high for homogeneous (intraclass correlation coefficient 0.862, P=0.003) and inhomogeneous (intraclass correlation coefficient 0.812, P=0.004) VCMs.ConclusionMagnetic resonance imaging–based whole‐heart IPM enables accurate spatial localization of sinus rhythm and premature ventricular contractions comparable to electroanatomic mapping. An inhomogeneous VCM improved IPM accuracy.

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Inventory of Digital Repositories for Research Output in the EUa m s t e r d a m u n i v e r s i t y p r e s s