Shuyu Liang, Ziyan Zhai, Xingmiao Feng, Xiaozhi Sun, Jingxuan Jiao, Yuan Gao, Kai Meng
Development of an index system for the scientific literacy of medical staff: a modified Delphi study in China
BMC medical education
chronic kidney disease ckd also known chronic renal disease illness affects majority adults defined progressive decrease kidney function time particularly diabetes high blood pressure metaheuristic mh algorithms based machine learning classifiers become reliable medical treatment weighted mean vectors info recently developed mh suffers fall local optimal slow convergence speed therefore improve info modified info minfo two enhancement strategies developed developed variant utilizes oppositionbased learning obl improve local search ability avoid trapping local optimum dynamic candidate solution dcs used overcome premature convergence problem info achieve appropriate balance exploration exploitation ability performance proposed minfo based knearest neighbor knn classifier evaluated complex cec22 test suite applied predict chronic kidney disease ckd datasets extracted uci statistical results revealed superiority minfo compared several wellknown mh algorithms including harris hawks optimization hho hunger games search hgs algorithm mothflame optimization mfo algorithm whale optimization algorithm woa sine cosine algorithm sca gradientbased optimizer gbo original info algorithm according knowledge paper first sort try employing proposed minfo solving cec22 test suite furthermore experimental results minfoknn classifying two ckd datasets demonstrated superiority overall classification accuracy 9317 two ckd datasets competitors