Commentary: Can machine learning reduce readmissions after esophagectomy? A consummation devoutly to be wished
J Thorac Cardiovasc Surg
.
2021 Jun;161(6):1944-1945.
doi: 10.1016/j.jtcvs.2020.05.054.
Epub 2020 Jun 1.
Authors
Nasser Altorki
1
,
Art Sedrakyan
2
Affiliations
1
Thoracic Surgery, Weill Cornell Medicine-New York Presbyterian Hospital, New York, NY. Electronic address: nkaltork@med.cornell.edu.
2
Healthcare Policy and Research, Weill Cornell Medicine, New York, NY.
PMID:
32711979
DOI:
10.1016/j.jtcvs.2020.05.054
No abstract available
Publication types
Editorial
Research Support, N.I.H., Extramural
Comment
MeSH terms
Esophagectomy* / adverse effects
Humans
Machine Learning
Patient Readmission*
Risk Factors
Grants and funding
U01 FD006936/FD/FDA HHS/United States
UG3 CA244697/CA/NCI NIH HHS/United States