Author:
Maltseva Daria,Chen Stephen,Lex Johnathan,Abbas Aazad,Whyne Cari
Publisher
Springer Nature Singapore
Reference27 articles.
1. Abbas, A., et al.: Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty. Int. J. Med. Inf. 158, 104670 (2022)
2. Association, H.F.M., et al.: Achieving operating room efficiency through process integration. Healthcare Finan. Manage. J. Healthcare Finan. Manage. Assoc. 57(3), 1–112 (2003)
3. Bovim, T.R., Christiansen, M., Gullhav, A.N., Range, T.M., Hellemo, L.: Stochastic master surgery scheduling. Eur. J. Oper. Res. 285(2), 695–711 (2020)
4. Britt, J., Baki, M.F., Azab, A., Chaouch, A., Li, X.: A stochastic hierarchical approach for the master surgical scheduling problem. Comput. Ind. Eng. 158, 107385 (2021)
5. Childers, C.P., Maggard-Gibbons, M.: Understanding costs of care in the operating room. JAMA Surg. 153(4), e176233–e176233 (2018)