| Li YC, HuangPJ |
------>authors3_c= ------>paper_class1=1 ------>Impact_Factor=2.612 ------>paper_class3=2 ------>paper_class2=1 ------>vol= ------>confirm_bywho=None ------>insert_bywho=jack ------>Jurnal_Rank=5.6 ------>authors4_c= ------>comm_author=1 ------>patent_EDate=None ------>authors5_c= ------>publish_day=1 ------>paper_class2Letter=None ------>page2=469 ------>medlineContent= ------>unit=000 ------>insert_date=20000620 ------>iam=1 ------>update_date= ------>author=??? ------>change_event=2 ------>ISSN= ------>authors_c= ------>score=500 ------>journal_name=Journal of the American Medical Informatics Association, Supplement ------>paper_name=Automated Transformation of Probabilistic Knowledge for a Medical Diagnostic System ------>confirm_date=None ------>tch_id=084004 ------>pmid=7950028 ------>page1=465 ------>fullAbstract=Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains. ------>tmu_sno=None ------>sno=2042 ------>authors2= ------>authors3= ------>authors4= ------>authors5= ------>authors6= ------>authors6_c= ------>authors=Li YC, HuangPJ ------>delete_flag=0 ------>SCI_JNo=None ------>authors2_c= ------>publish_area=0 ------>updateTitle=Automated transformation of probabilistic knowledge for a medical diagnostic system. ------>language=2 ------>check_flag= ------>submit_date= ------>country=None ------>no= ------>patent_SDate=None ------>update_bywho= ------>publish_year=1994 ------>submit_flag= ------>publish_month=1 |