Machine learning-based prediction of fainting during blood donations using donor properties and weather data as features

HIGHLIGHTS

SUMMARY

The study aimed to predict fainting in voluntary blood donors and to identify potential factors accounting for the occurrence of a vasovagal reaction during blood donation using modern machine_learning algorithms. Other studies on machine_learning focus on eligibility of donors or use elaborate donor observation. Statistics For the prediction of fainting, the authors employed the model selection procedure for seven different, state-of-the-art machine_learning methods: random forests, artificial Data from all whole blood and apheresis (thrombocytes, plasma, no erythrocyte apheresis) donors from January 2017 to December 2020 of the Red Cross blood donation . . .

 



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