| Shieh JS |
------>authors3_c= ------>paper_class1=1 ------>Impact_Factor=2.496 ------>paper_class3=2 ------>paper_class2=1 ------>vol=54 ------>confirm_bywho=tlc ------>insert_bywho=yrwen ------>Jurnal_Rank=29.4 ------>authors4_c= ------>comm_author= ------>patent_EDate=None ------>authors5_c= ------>publish_day=1 ------>paper_class2Letter=None ------>page2=32 ------>medlineContent= ------>unit=E0100 ------>insert_date=20080508 ------>iam=3 ------>update_date=None ------>author=??? ------>change_event=4 ------>ISSN= ------>authors_c= ------>score=500 ------>journal_name=IEEE Transactions on Biomedical Engineering ------>paper_name=A novel fuzzy pain demand index derived from patient-controlled analgesia for postoperative pain. ------>confirm_date=20090814 ------>tch_id=096124 ------>pmid=18075028 ------>page1=23 ------>fullAbstract=A multilayer hierarchical structure for an intelligent analysis system is described in this paper. Four levels (patients~, measurement, Web-based, and interpreting) are used to collect massive amounts from clinical information and analyze it with both traditional and artificial intelligent methods. To support this, a novel fuzzy pain demand (FPD) index derived from the interval of each bolus of patient-controlled analgesia (PCA) is designed and documented in a large-scale clinical survey. The FPD index is modeled according to a fuzzy modeling algorithm to interpret the self-titration of the drug delivery. A total of 255 patients receiving intravenous PCA using morphine (1 mg/ml) tested this index by offline analysis from this system. We found the FPD index modeled from a fuzzy modeling algorithm to interpret the self-titration of the drug delivery can show the patients~ dynamic demand and past efforts to overcome the postoperative pain. Moreover, it could become an online system to monitor patients~ demand or intent to treat their pain so these factors could be entered into a patient~s chart along with temperature, blood pressure, pulse, and respiration rates when medical practitioners check the patients. ------>tmu_sno=None ------>sno=18601 ------>authors2=Dai CY ------>authors3=Wen YR ------>authors4=Sun WZ ------>authors5= ------>authors6= ------>authors6_c= ------>authors=Shieh JS ------>delete_flag=0 ------>SCI_JNo=None ------>authors2_c= ------>publish_area=0 ------>updateTitle=A novel fuzzy pain demand index derived from patient-controlled analgesia for postoperative pain. ------>language=2 ------>check_flag=None ------>submit_date=None ------>country=None ------>no=21 ------>patent_SDate=None ------>update_bywho=None ------>publish_year=2007 ------>submit_flag=None ------>publish_month=1 |