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Open Access
Peer-reviewed
Research Article
Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era
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Lathan Liou,
Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing
Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
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Elizabeth Mostofsky,
Roles Data curation, Project administration, Resources, Writing – review & editing
Affiliation Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Laura Lehman,
Roles Writing – review & editing
Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America, Department of Neurology, Boston Children’s Hospital, Boston, Massachusetts, United States of America
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Soziema Salia,
Roles Writing – review & editing
Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Department of Internal Medicine, Cape Coast Teaching Hospital, Cape Coast, Ghana
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Francisco J. Barrera,
Roles Writing – review & editing
Affiliation Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Ying Wei,
Roles Writing – review & editing
Affiliation Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Amal Cheema,
Roles Writing – review & editing
Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, United States of America
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Anuradha Lala,
Roles Methodology, Supervision, Writing – review & editing
Affiliation Zena and Michael A. Wiener Cardiovascular Institute and Department of Population Health Science and Policy, Mount Sinai, New York, New York, United States of America
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Andrew Beam ,
Contributed equally to this work with: Andrew Beam, Murray A. Mittleman
Roles Methodology, Supervision, Writing – review & editing
Affiliation Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Murray A. Mittleman
Contributed equally to this work with: Andrew Beam, Murray A. Mittleman
Roles Conceptualization, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing
* E-mail: mmittlem@hsph.harvard.edu
Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America, Department of Medicine, Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
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Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era
- Lathan Liou,
- Elizabeth Mostofsky,
- Laura Lehman,
- Soziema Salia,
- Francisco J. Barrera,
- Ying Wei,
- Amal Cheema,
- Anuradha Lala,
- Andrew Beam,
- Murray A. Mittleman
- Published: January 7, 2025
- https://doi.org/10.1371/journal.pone.0313600