Publications by authors named "Yoshiaki Ara"
Article Synopsis
- A study investigates how to use machine learning to predict prescription errors in dosing oral prednisolone, a high-risk drug, due to the common issue of wrong doses causing harm to patients.
- Data was collected from electronic medical records, analyzed using cluster analysis to group similar prescribing patterns, and different machine learning models were tested to improve accuracy.
- Results showed that preprocessing the data with the SMOTE method enhanced model performance, with the best results coming from the BRF model (ROC-AUC: 0.917) and SVM after preprocessing (ROC-AUC: 0.820).
Objectives The influential factors for anti-severe acute respiratory syndrome coronavirus 2 spike protein antibody (S-ab) levels were assessed after the administration of BNT162b2 mRNA coronavirus disease-2019 (COVID-19) vaccine at short and medium terms. Methods A total of 470 healthcare workers (118 males, mean age 41.0±11.
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