Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism.
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| Title: | Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism. |
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| Authors: | Eisenhofer G; Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.; Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany., Durán C; Biomedical Cybernetics Group, Biotechnology Center, Center for Molecular and Cellular Bioengineering, Center for Systems Biology Dresden, Department of Physics, Technische Universität Dresden, Dresden, Germany., Cannistraci CV; Biomedical Cybernetics Group, Biotechnology Center, Center for Molecular and Cellular Bioengineering, Center for Systems Biology Dresden, Department of Physics, Technische Universität Dresden, Dresden, Germany.; Center for Complex Network Intelligence Laboratory at the Tsinghua Laboratory of Brain and Intelligence, Department of Bioengineering, Tsinghua University, Beijing, China., Peitzsch M; Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany., Williams TA; Division of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Turin, Italy.; Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany., Riester A; Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany., Burrello J; Division of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Turin, Italy., Buffolo F; Division of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Turin, Italy., Prejbisz A; Department of Hypertension, Institute of Cardiology, Warsaw, Poland., Beuschlein F; Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany.; Department of Endocrinology, Diabetology, and Clinical Nutrition, UniversitätsSpital Zürich, Zürich, Switzerland., Januszewicz A; Department of Hypertension, Institute of Cardiology, Warsaw, Poland., Mulatero P; Division of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Turin, Italy., Lenders JWM; Department of Internal Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.; Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands., Reincke M; Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany. |
| Source: | JAMA network open [JAMA Netw Open] 2020 Sep 01; Vol. 3 (9), pp. e2016209. Date of Electronic Publication: 2020 Sep 01. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: American Medical Association Country of Publication: United States NLM ID: 101729235 Publication Model: Electronic Cited Medium: Internet ISSN: 2574-3805 (Electronic) Linking ISSN: 25743805 NLM ISO Abbreviation: JAMA Netw Open Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2574-3805 |
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| DOI: | 10.1001/jamanetworkopen.2020.16209 |
