Comparison of machine learning algorithms to predict length of hospital stay in patients undergoing heart bypass surgery

Author:

Profeta Martina1,Maria Ponsiglione Alfonso1,Ponsiglione Cristina2,Ferrucci Giuseppe3,Giglio Cristiana4,Borrelli Anna3

Affiliation:

1. Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Italy

2. Department of Industrial Engineering, University of Naples Federico II, Italy

3. San Giovanni di Dio e Ruggi d'Aragona University Hospital, Italy

4. University of Rome La Sapienza, Italy

Publisher

ACM

Reference31 articles.

1. Coronary artery bypass graft surgery: the past, present, and future of myocardial revascularisation;Diodato M;Surg. Res. Pract.,2014

2. Epidemiology of coronary artery bypass grafting at the Hospital Beneficência Portuguesa;Sousa;São Paulo Rev. Bras. Cir. Cardiovasc. Orgao Of. Soc. Bras. Cir. Cardiovasc.,2015

3. Lazar Harold L. Fitzgerald Carmel Gross Stacy Heeren Tim Aldea Gabriel S. and Shemin Richard J. 1995 Determinants of Length of Stay After Coronary Artery Bypass Graft Surgery Circulation 92 20–4 Lazar Harold L. Fitzgerald Carmel Gross Stacy Heeren Tim Aldea Gabriel S. and Shemin Richard J. 1995 Determinants of Length of Stay After Coronary Artery Bypass Graft Surgery Circulation 92 20–4

4. Prediction of Costs and Length of Stay in Coronary Artery Bypass Grafting

5. Aortocoronary bypass graft patency assessed by coronary computed tomography angiography–unicentric study;Luca C;Rev. Med. Chir. Soc. Med. Nat. Iasi,2014

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