Automated real-time detection of lung sliding using artificial intelligence: a prospective diagnostic accuracy study

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dc.catalogadorjwg
dc.contributor.authorClausdorff Fiedler, Hans Jurgen
dc.contributor.authorPrager, Ross
dc.contributor.authorSmith, Delaney
dc.contributor.authorWu, Derek
dc.contributor.authorDave, Chintan
dc.contributor.authorTschirhart, Jared
dc.contributor.authorWu, Ben
dc.contributor.authorVanBerlo, Blake
dc.contributor.authorMalthaner, Richard
dc.contributor.authorArntfield, Robert
dc.date.accessioned2024-03-14T17:24:49Z
dc.date.available2024-03-14T17:24:49Z
dc.date.issued2024
dc.description.abstractAs mental health issues continue to rise in Latin America, the need for research in this field becomes increasingly pressing. This study aimed to explore the perceived barriers and resources for research and publications among psychiatrists and psychiatry trainees from nine Spanish-speaking countries in South America. Data was collected through an anonymous online survey and analyzed using descriptive methods and the SPSS Statistical package. In total, 214 responses were analyzed. Among the participating psychiatrists, 61.8% reported having led a research project and 74.7% of them reported having led an academic publication. As for the psychiatry trainees, 26% reported having conducted research and 41.5% reported having published or attempted to publish an academic paper. When available, having access to research training, protected research time and mentorship opportunities were significant resources for research. Further support is needed in terms of funding, training, protected research time and mentorship opportunities. However, despite their efforts to participate in the global mental health discussion, Latin American psychiatrists and psychiatry trainees remain largely underrepresented in the literature.
dc.fuente.origenORCID
dc.identifier.doi10.1016/j.chest.2024.02.011
dc.identifier.urihttp://dx.doi.org/10.1016/j.chest.2024.02.011
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/84412
dc.information.autorucEscuela de Medicina; Clausdorff Fiedler, Hans Jurgen; 0000-0002-0571-7815; 172140
dc.language.isoen
dc.nota.accesoContenido parcial
dc.rightsacceso restringido
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectArtificial intelligence
dc.subjectLung sliding
dc.subjectLung ultrasound
dc.subjectPneumothorax
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.titleAutomated real-time detection of lung sliding using artificial intelligence: a prospective diagnostic accuracy study
dc.typeartículo
sipa.codpersvinculados172140
sipa.trazabilidadORCID;2024-02-19
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