Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm
Joon Lee; Sapna Govindan; Leo Anthony Celi; Kamal R. Khabbaz; Balachundhar Subramaniam · 2013 · World Journal of Cardiovascular Surgery
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
OBJECTIVE: To develop a customized short LOS (<6 days) prediction model for geriatric patients receiving cardiac surgery, using local data and a computational feature selection algorithm. DESIGN: Utilization of a machine learning algorithm in a prospectively collected STS database consisting of patients who received cardiac surgery between January 2002 and June 2011. SETTING: Urban tertiary-care center. PARTICIPANTS: Geriatric patients aged 70 years or older at the time of cardiac surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Predefined morbidity and mortality events were collec
Abstract by Joon Lee; Sapna Govindan; Leo Anthony Celi; Kamal R. Khabbaz; Balachundhar Subramaniam, World Journal of Cardiovascular Surgery (2013) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.4236/wjcs.2013.35034