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A machine learning approach to predict the hospital length ..:
, In:
Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science
,
Marino, Marta Rosaria
;
Majolo, Massimo
;
Grasso, Marco
... - p. 54-58 , 2022
Link:
https://dl.acm.org/doi/10.1145/3571532.3571539
RT T1 <cTitle>Proceedings of the 2022 11th International Conference on Bioinformatics and Biomedical Science</cTitle>: T1 <Title>A machine learning approach to predict the hospital length of stay after kidney surgery</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3571539&Exemplar=1&LAN=DE A1 Marino, Marta Rosaria A1 Majolo, Massimo A1 Grasso, Marco A1 Russo, Giuseppe A1 Longo, Giuseppe A1 Triassi, Maria A1 Trunfio, Teresa Angela PB ACM YR 2022 K1 Applied computing K1 Life and medical sciences K1 Health informatics K1 Mathematics of computing K1 Mathematical software K1 Statistical software K1 Health care information systems K1 General and reference K1 Document types K1 General conference proceedings SP 54 OP 58 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3571532.3571539 DO https://dl.acm.org/doi/10.1145/3571532.3571539 SF ELIB - SuUB Bremen
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