Premium
Orthogonal search‐based rule extraction for modelling the decision to transfuse
Author(s) -
Etchells T. A.,
Harrison M. J.
Publication year - 2006
Publication title -
anaesthesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.839
H-Index - 117
eISSN - 1365-2044
pISSN - 0003-2409
DOI - 10.1111/j.1365-2044.2006.04545.x
Subject(s) - medicine , predictive value , decision rule , surgery , artificial intelligence , computer science
Summary Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search‐based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100‐mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on‐going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb < 94 g.l −1 ; 2. ROTH > 13 mm and Hb < 87 g.l −1 ; 3. ROTH > 38 mm, Hb < 102 g.l −1 and OGH; 4. Hb < 78 g.l −1 .