Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients.
- Published in:
- NPJ Digital Medicine, 2019, v. 2, n. 1, p. N.PAG, doi. 10.1038/s41746-019-0192-z
- By:
- Publication type:
- Article
Works matching AU Sauer, Christopher Martin
Results: 7
1
2
Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital.
- Published in:
- Cancer Research & Treatment, 2019, v. 51, n. 3, p. 973, doi. 10.4143/crt.2018.360
- By:
- Publication type:
- Article
3
Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study.
- Published in:
- Journal of Medical Internet Research, 2024, v. 26, p. 1, doi. 10.2196/56382
- By:
- Publication type:
- Article
4
Establishing Medical Intelligence—Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study.
- Published in:
- Journal of Medical Internet Research, 2024, v. 26, p. 1, doi. 10.2196/55148
- By:
- Publication type:
- Article
5
Why federated learning will do little to overcome the deeply embedded biases in clinical medicine.
- Published in:
- 2024
- By:
- Publication type:
- Letter
6
Feature selection and prediction of treatment failure in tuberculosis.
- Published in:
- PLoS ONE, 2018, v. 13, n. 11, p. 1, doi. 10.1371/journal.pone.0207491
- By:
- Publication type:
- Article
7
Boosting Clinical Decision-making: Machine Learning for Intensive Care Unit Discharge.
- Published in:
- 2018
- By:
- Publication type:
- Editorial