A machine learning approach for the prediction of pulmonary hypertension

Andreas Leha; Kristian Hellenkamp; Bernhard Unsöld; Sitali Mushemi-Blake; Ajay M. Shah; Gerd Hasenfuß; Tim Seidler

doi:10.1371/journal.pone.0224453

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Open Access

Peer-reviewed

Research Article

A machine learning approach for the prediction of pulmonary hypertension

Andreas Leha,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
⨯
Kristian Hellenkamp,

Roles Data curation, Investigation, Validation, Writing – original draft

Affiliation Clinic for Cardiology and Pulmonology/Heart Center, University Medical Center Göttingen, Göttingen, Germany
⨯
Bernhard Unsöld,

Roles Data curation

Affiliation Department of Internal Medicine II, University of Regensburg, Regensburg, Germany
⨯
Sitali Mushemi-Blake,

Roles Data curation, Investigation, Resources

Affiliation King’s College London British Heart Foundation Centre, School of Cardiovascular Medicine & Sciences, London, England, United Kingdom
⨯
Ajay M. Shah,

Roles Conceptualization, Data curation, Writing – original draft

Affiliation King’s College London British Heart Foundation Centre, School of Cardiovascular Medicine & Sciences, London, England, United Kingdom
⨯
Gerd Hasenfuß,

Roles Funding acquisition, Resources, Writing – original draft

Affiliations Clinic for Cardiology and Pulmonology/Heart Center, University Medical Center Göttingen, Göttingen, Germany, DZHK (German Centre for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany
⨯
Tim Seidler

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: tim.seidler@med.uni-goettingen.de

Affiliations Clinic for Cardiology and Pulmonology/Heart Center, University Medical Center Göttingen, Göttingen, Germany, DZHK (German Centre for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany

http://orcid.org/0000-0002-6158-5087

⨯

A machine learning approach for the prediction of pulmonary hypertension

Andreas Leha,
Kristian Hellenkamp,
Bernhard Unsöld,
Sitali Mushemi-Blake,
Ajay M. Shah,
Gerd Hasenfuß,
Tim Seidler

Published: October 25, 2019
https://doi.org/10.1371/journal.pone.0224453

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