Johann Engelbrecht, Marcelo C Borba, Gabriele Kaiser
Will we ever teach mathematics again in the way we used to before the pandemic?
ZDM : the international journal on mathematics education
enhanced recovery surgery eras accelerate patient recovery however little research done optimizing erasrelated measures measures interact bayesian network bn graphical model describes dependencies variables also model uncertainty reasoning study aimed develop method optimizing anesthetic decisions eras investigate relationship anesthetic decisions outcomes first assuming indicators used independent effects combinations single indicators analyzed based bn additionally impact indicators outcomes selected statistical tests based previously selected indicators bayesian network constructed using proposed structure learning method based strongly connected components scc local structure determination hill climbing twice lshct adjusted according experts knowledge finally relationship analyzed proposed method validated real clinical data patients benign gynecological tumors 3 hospitals china postoperative length stay los total cost tc chosen outcomes experimental results show eras protocol pivotal indicators influencing los tc identifying relationship indicators help anesthesiologists optimize eras protocol make individualized decisions