ABSTRACT
Objective To design and implement a medication recommending system for chronic hepatitis B (CHB) in order to predict CHB inpatient clinical medication.Methods The system was designed and realized with improved ML-KNN algorithm,training the multi-label data set extracted from HIS database,Java framework technology as well as MyEclipse9.0 platform.Results The system could predict the clinical medication of the CHB inpatient,and enhanced the CHB inpatient satisfaction greatly.Conclusion The system is of practical value for the the clinical medication of the CHB inpatient,and thus is worthy promoting practically.
ABSTRACT
Objective To design and implement a medication recommending system for chronic hepatitis B (CHB) in order to predict CHB inpatient clinical medication.Methods The system was designed and realized with improved ML-KNN algorithm,training the multi-label data set extracted from HIS database,Java framework technology as well as MyEclipse9.0 platform.Results The system could predict the clinical medication of the CHB inpatient,and enhanced the CHB inpatient satisfaction greatly.Conclusion The system is of practical value for the the clinical medication of the CHB inpatient,and thus is worthy promoting practically.