Researchers enhanced the accuracy of mortality predictions in emergency departments by employing advanced data-synthesis techniques and machine-learning models.
By Susha Cheriyedath, M.Sc.Sep 14 2023Reviewed by Sophia Coveney In a recent study published in Scientific Reports, a group of researchers enhanced the accuracy of mortality predictions in emergency departments by employing advanced data-synthesis techniques and machine learning models.
About the study The present study utilized data from 7,325 individuals who visited Yonsei Severance Hospital’s ED in Seoul, South Korea between January and June 2020. As a designated coronavirus disease 2019 screening clinic, the hospital was tasked with managing severe cases. The data was collected by authorized medical personnel via the hospital’s electronic system.
Related StoriesThe initial dataset had 7,325 patients, but 1,543 records had missing features, leading to a refined dataset of 5,782 records. For the machine learning system’s training and evaluation, data was divided into training and test sets. The present study emphasized the F1 score as the primary evaluation metric over conventional accuracy scores due to its relevance in imbalanced medical datasets.
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