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  <text> <status value="extensions"/> <div xmlns="http://www.w3.org/1999/xhtml"><p> <b> Generated Narrative: Citation</b> <a name="citation-example-research-doi"> </a> </p> <div style="display: inline-block; background-color: #d9e0e7; padding: 6px; margin: 4px; border:
       1px solid #8da1b4; border-radius: 5px; line-height: 60%"><p style="margin-bottom: 0px">Resource Citation &quot;citation-example-research-doi&quot; </p> </div> <p> <b> StructureDefinition Work Group</b> : cds</p> <p> <b> identifier</b> : FEvIR Object Identifier: 60</p> <p> <b> name</b> : NInFEACitation</p> <p> <b> title</b> : NInFEA Citation</p> <p> <b> status</b> : active</p> <p> <b> date</b> : 2021-09-24T10:41:01.74Z</p> <p> <b> publisher</b> : HL7 International / Clinical Decision Support</p> <p> <b> contact</b> : <a href="http://www.hl7.org/Special/committees/dss">http://www.hl7.org/Special/committees/dss</a> </p> <p> <b> description</b> : A citation of a dataset</p> <p> <b> copyright</b> : https://creativecommons.org/licenses/by-nc-sa/4.0/</p> <blockquote> <p> <b> summary</b> </p> <p> <b> style</b> : as reported on PhysioNet <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> text</b> : Pani, D., Sulas, E., Urru, M., Sameni, R., Raffo, L., &amp; Tumbarello, R. (2020).
           NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology
           Research (version 1.0.0). PhysioNet. https://doi.org/10.13026/c4n5-3b04.</p> </blockquote> <blockquote> <p> <b> summary</b> </p> <p> <b> style</b> : Computable Publishing <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (citation-summary-style#comppub)</span> </p> <p> <b> text</b> : NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology
           Research [Dataset], version 1.0.0. Contributors: Danilo Pani, Eleonora Sulas, Monica
           Urru, Reza Sameni, Luigi Raffo, Roberto Tumbarello. In: PhysioNet, DOI 10.13026/c4n5-3b04.
           Published November 12, 2020. Accessed March 17, 2021. Available at: https://physionet.org/con
          tent/ninfea/1.0.0/.</p> </blockquote> <blockquote> <p> <b> citedArtifact</b> </p> <p> <b> identifier</b> : id: 10.13026/c4n5-3b04</p> <p> <b> relatedIdentifier</b> : id: 10.1038/s41597-021-00811-3</p> <p> <b> dateAccessed</b> : 2021-03-17</p> <h3> Versions</h3> <table class="grid"><tr> <td style="display: none">-</td> <td> <b> Value</b> </td> </tr> <tr> <td style="display: none">*</td> <td> 1.0.0</td> </tr> </table> <h3> Titles</h3> <table class="grid"><tr> <td style="display: none">-</td> <td> <b> Type</b> </td> <td> <b> Language</b> </td> <td> <b> Text</b> </td> </tr> <tr> <td style="display: none">*</td> <td> primary-human-use <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </td> <td> English <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (Tags for the Identification of Languages[4.0.1]#en)</span> </td> <td> NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology
               Research</td> </tr> </table> <h3> Abstracts</h3> <table class="grid"><tr> <td style="display: none">-</td> <td> <b> Type</b> </td> <td> <b> Language</b> </td> <td> <b> Text</b> </td> </tr> <tr> <td style="display: none">*</td> <td> Primary human use <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-cited-artifact-abstract-type.html">Cited Artifact Abstract Type</a> #primary-human-use)</span> </td> <td> English <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="http://terminology.hl7.org/5.4.0/CodeSystem-v3-ietf3066.html">Tags for the Identification of Languages</a> #en)</span> </td> <td> The development of algorithms for the extraction of the foetal ECG (fECG) from
               non-invasive recordings is hampered by the lack of publicly-available reference
               datasets, which could be used to benchmark different algorithms while providing
               a ground truth on the foetal heart activity when an invasive scalp lead is unavailable.
               By enriching the electrophysiological recordings with simultaneous multimodal signals,
               these datasets could also help the investigation of the foetal cardiac physiology,
               providing ground truth for the analysis in early pregnancy, when the fECG is not
               directly accessible.  The Non-Invasive Multimodal Foetal ECG-Doppler Dataset for
               Antenatal Cardiology Research (NInFEA) is the first open-access dataset featuring
               simultaneous non-invasive electrophysiological recordings, fetal pulsed-wave Doppler
               (PWD) and maternal respiration signals. The dataset includes 60 entries from 39
               voluntary pregnant women, between the 21st and the 27th week of gestation. Every
               entry is composed of 27 electrophysiological channels (2048 Hz, 22 bits, acquired
               by means of the TMSi Porti7 system), maternal respiration signal (through a resistive
               thoracic belt), synchronised foetal trans-abdominal PWD and clinical annotations
               provided by expert clinicians at the time of the signal collection.</td> </tr> </table> <blockquote> <p> <b> relatesTo</b> </p> <p> <b> type</b> : derived-from</p> <p> <b> classifier</b> : original publication <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> citation</b> : Sulas, E., Urru, M., Tumbarello, R., Raffo, L., Sameni, R., Pani, D., A non-invasive
             multimodal foetal ECG–Doppler dataset for antenatal cardiology research. Sci Data
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            ninfea/1.0.0/LICENSE.txt</p> </blockquote> <blockquote> <p> <b> webLocation</b> </p> <p> <b> classifier</b> : Webpage <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-artifact-url-classifier.html">Artifact Url Classifier[6.0.0]</a> #webpage)</span> </p> <p> <b> url</b> : <a href="https://physionet.org/content/ninfea/1.0.0/">https://physionet.org/content/ninfea/1.0.0/</a> </p> </blockquote> <blockquote> <p> <b> webLocation</b> </p> <p> <b> classifier</b> : DOI Based <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-artifact-url-classifier.html">Artifact Url Classifier[6.0.0]</a> #doi-based)</span> </p> <p> <b> url</b> : <a href="https://doi.org/10.13026/c4n5-3b04">https://doi.org/10.13026/c4n5-3b04</a> </p> </blockquote> <blockquote> <p> <b> webLocation</b> </p> <p> <b> classifier</b> : original publication <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-artifact-url-classifier.html">Artifact Url Classifier[6.0.0]</a> #doi-based &quot;DOI Based&quot;)</span> </p> <p> <b> url</b> : <a href="https://doi.org/10.1038/s41597-021-00811-3">https://doi.org/10.1038/s41597-021-00811-3</a> </p> </blockquote> <blockquote> <p> <b> webLocation</b> </p> <p> <b> classifier</b> : Compressed file <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-artifact-url-classifier.html">Artifact Url Classifier[6.0.0]</a> #compressed-file)</span> </p> <p> <b> url</b> : <a href="https://physionet.org/static/published-projects/ninfea/ninfea-non-invasive-multimodal-foetal-
            ecg-doppler-dataset-for-antenatal-cardiology-research-1.0.0.zip">https://physionet.org/static/published-projects/ninfea/ninfea-non-invasive-multimodal-foetal-
              ecg-doppler-dataset-for-antenatal-cardiology-research-1.0.0.zip</a> </p> </blockquote> <blockquote> <p> <b> webLocation</b> </p> <p> <b> classifier</b> : DOI-for-metadata <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> url</b> : <a href="https://doi.org/10.6084/m9.figshare.13283492">https://doi.org/10.6084/m9.figshare.13283492</a> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> classifier</b> : Knowledge Artifact Type <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-cited-artifact-classification-type.html">Cited Artifact Classification Type</a> #knowledge-artifact-type)</span> , Dataset <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-citation-artifact-classifier.html">Citation Artifact Classifier[6.0.0]</a> #D064886)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : ecg <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (efo#EFO_0004327 &quot;electrocardiography&quot;)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : foetus <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (obo#FMA_63919)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : pwd <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : doppler <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : foetal ecg <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : maternal ecg <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : pwd envelope <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : non-invasive <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : cardiology <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="https://browser.ihtsdotools.org/">SNOMED CT</a> #394579002 &quot;Cardiology (qualifier value)&quot;)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : early pregnancy <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="https://browser.ihtsdotools.org/">SNOMED CT</a> #314204000 &quot;Early stage of pregnancy (finding)&quot;)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : antenatal <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : topic <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : fecg <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="https://browser.ihtsdotools.org/">SNOMED CT</a> #75444003 &quot;Fetal electrocardiogram (procedure)&quot;)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : subject type <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : Homo sapiens <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (NCBITAXON#9606)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : use context <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : gestational age <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (efo#EFO_0005112)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : use context <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : electrocardiography <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (efo#EFO_0004327)</span> </p> </blockquote> <blockquote> <p> <b> classification</b> </p> <p> <b> type</b> : use context <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> classifier</b> : heart electrical impulse conduction trait <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (obo#VT_2000017)</span> </p> </blockquote> <blockquote> <p> <b> contributorship</b> </p> <blockquote> <p> <b> summary</b> </p> <p> <b> type</b> : Author string <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> (<a href="codesystem-contributor-summary-type.html">Contributor Summary Type[6.0.0]</a> #author-string)</span> </p> <p> <b> source</b> : copied-from-article <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> value</b> : Danilo Pani, Eleonora Sulas, Monica Urru, Reza Sameni, Luigi Raffo, Roberto Tumbarello</p> </blockquote> <blockquote> <p> <b> summary</b> </p> <p> <b> type</b> : acknowledgements <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> source</b> : copied-from-article <span style="background: LightGoldenRodYellow; margin: 4px; border: 1px solid khaki"> ()</span> </p> <p> <b> value</b> : The authors wish to thank the Pediatric Cardiology and Congenital Heart Disease
               Unit, Brotzu Hospital (Cagliari, Italy), where the dataset was collected, and all
               the voluntary pregnant women for their kindness in giving their signals for this
               research. The authors gratefully thank Alessandra Cadoni, Graziella Secchi, Luisa
               Aru, Elisa Farris, Chiara Fenu, Elisa Gusai, Giulia Baldazzi, Giulia Pili for their
               support in the recording of the signals included in this dataset.  Part of this
               research was supported by the Italian Government—Progetti di InteresseNazionale
               (PRIN) under the grant agreement 2017RR5EW3 - ICT4MOMs project.  Eleonora Sulas
               is grateful to Sardinia Regional Government for supporting her PhD scholarship
               (P.O.R.F.S.E., European Social Fund 2014-2020).  Reza Sameni acknowledges the funding
               from the European Research Council Advanced Grant Number 320684, on Challenges
               in the Extraction and Separation of Sources (CHESS) for his contribution in this
               research, provided during his appointment at GIPSA-lab, Grenoble Alpes University,
               Grenoble, France.</p> </blockquote> </blockquote> </blockquote> </div> </text> <extension url="http://hl7.org/fhir/StructureDefinition/structuredefinition-wg"><valueCode value="cds"/> </extension> 
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     NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology
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     Research [Dataset], version 1.0.0. Contributors: Danilo Pani, Eleonora Sulas, Monica
     Urru, Reza Sameni, Luigi Raffo, Roberto Tumbarello. In: PhysioNet, DOI 10.13026/c4n5-3b04.
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      <text value="The development of algorithms for the extraction of the foetal ECG (fECG) from
       non-invasive recordings is hampered by the lack of publicly-available reference
       datasets, which could be used to benchmark different algorithms while providing
       a ground truth on the foetal heart activity when an invasive scalp lead is unavailable.
       By enriching the electrophysiological recordings with simultaneous multimodal signals,
       these datasets could also help the investigation of the foetal cardiac physiology,
       providing ground truth for the analysis in early pregnancy, when the fECG is not
       directly accessible.  The Non-Invasive Multimodal Foetal ECG-Doppler Dataset for
       Antenatal Cardiology Research (NInFEA) is the first open-access dataset featuring
       simultaneous non-invasive electrophysiological recordings, fetal pulsed-wave Doppler
       (PWD) and maternal respiration signals. The dataset includes 60 entries from 39
       voluntary pregnant women, between the 21st and the 27th week of gestation. Every
       entry is composed of 27 electrophysiological channels (2048 Hz, 22 bits, acquired
       by means of the TMSi Porti7 system), maternal respiration signal (through a resistive
       thoracic belt), synchronised foetal trans-abdominal PWD and clinical annotations
       provided by expert clinicians at the time of the signal collection."/> 
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       8, 30 (2021). https://doi.org/10.1038/s41597-021-00811-3"/> 
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        <value value="The authors wish to thank the Pediatric Cardiology and Congenital Heart Disease
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         support in the recording of the signals included in this dataset.  Part of this
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         (PRIN) under the grant agreement 2017RR5EW3 - ICT4MOMs project.  Eleonora Sulas
         is grateful to Sardinia Regional Government for supporting her PhD scholarship
         (P.O.R.F.S.E., European Social Fund 2014-2020).  Reza Sameni acknowledges the funding
         from the European Research Council Advanced Grant Number 320684, on Challenges
         in the Extraction and Separation of Sources (CHESS) for his contribution in this
         research, provided during his appointment at GIPSA-lab, Grenoble Alpes University,
         Grenoble, France."/> 
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