Computer algorithm can match physicians' decisions about blood transfusions

Yao, Cifuentes, Zheng, Yan (2019) Computer algorithm can match physicians' decisions about blood transfusions J Transl Med (IF: 7.4) 17(1) 340

Abstract

Checking appropriateness of blood transfusion for quality assurance required enormous usage of time and human resources from the healthcare system. We report here a new machine learning algorithm for checking blood transfusion quality.The multilayer perceptron neural network (MLPNN) was designed to learn an expert's judgement from 4946 clinical cases. The accuracy in predicting the blood transfusion was then reported.We achieved a 96.8% overall accuracy rate, with a 99% match rate to the experts' judgement on those appropriate cases and 90.9% on the inappropriate cases.Machine learning algorithm can accurately match to human judgement by feeding in pre-surgical information and key laboratory variables.

Links

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785926
http://www.ncbi.nlm.nih.gov/pubmed/31601245
http://dx.doi.org/10.1186/s12967-019-2085-y

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