Sabin Kumar Ranabhat, Mohan Lal Kunjukrishnan, Muskan Dubey, Vernon Curran, Arun Kumar Dubey, Neelam Dwivedi
Exploring the usage of learning resources by medical students in the basic science stage and their effect on academic performance
BMC medical education
macrophage activation syndrome mas secondary systemic lupus erythematosus sle severe lifethreatening complication early diagnosis mas particularly challenging study machine learning models diagnostic scoring card developed aid clinical decisionmaking using clinical characteristics retrospectively collected clinical data 188 patients either sle mas secondary sle 13 significant clinical predictor variables filtered using least absolute shrinkage selection operator lasso variables subsequently utilized inputs five machine learning models performance models evaluated using area receiver operating characteristic curve rocauc f1 score f2 score enhance clinical usability developed diagnostic scoring card based logistic regression lr analysis chisquare binning establishing probability thresholds stratification card additionally study collected data four domestic hospitals external validation among machine learning models lr model demonstrates highest level performance internal validation achieving rocauc 0998 f1 score 096 f2 score 0952 score card constructed identifies probability threshold score 49 achieving rocauc 0994 f2 score 0936 score results categorized five groups based diagnostic probability extremely low 5 low 525 normal 2575 high 7595 extremely high 95 external validation performance evaluation revealed support vector machine svm model outperformed models auc value 0947 scorecard model auc 0915 additionally established online assessment system early identification mas secondary sle machine learning models significantly improve diagnostic accuracy mas secondary sle diagnostic scorecard model facilitate personalized probabilistic predictions disease occurrence clinical environments