Hematochezia is one of common gastrointestinal complaint at the Emergency Department (ED). Causes may be due to upper (UGIB) or lower (LGIB) gastrointestinal tract bleeding. Here, clinical factors were studied to differentiate sites of bleeding in patients with hematochezia. All patients with an age of more than 18 years who were diagnosed with GIB at the ED, Ramathibodi Hospital, Thailand were enrolled. Patients who presented with hematochezia and received complete workups to identify causes of bleeding were studied and categorized as being in the UGIB or LGIB groups. There were 1,854 patients who presented with GIB at the ED. Of those, 76 patients presented with hematochezia; 30 patients were in the UGIB group, while 43 patients were in the LGIB group. Clinical variables between both groups were mostly comparable. Three clinical factors were significantly associated with UGIB causes in patients with hematochezia including systolic blood pressure, hematocrit level, and BUN/Cr ratio. The adjusted odds ratios for all three factors were 0.725 (per 5 mmHg increase), 0.751 (per 3% increase), and 1.11 (per unit increase). Physicians at the ED could use these clinical factors as a guide for further investigation in patients who presented with hematochezia.
SUMMARYThe development of ontology at the instance level requires the extraction of the terms defining the instances from various data sources. These instances then are linked to the concepts of the ontology, and relationships are created between these instances for the next step. However, before establishing links among data, ontology engineers must classify terms or instances from a web document into an ontology concept. The tool for help ontology engineer in this task is called ontology population. The present research is not suitable for ontology development applications, such as long time processing or analyzing large or noisy data sets. OntoPop system introduces a methodology to solve these problems, which comprises two parts. First, we select meaningful features from syntactic relations, which can produce more significant features than any other method. Second, we differentiate feature meaning and reduce noise based on latent semantic analysis. Experimental evaluation demonstrates that the OntoPop works well, significantly out-performing the accuracy of 49.64%, a learning accuracy of 76.93%, and executes time of 5.46 second/instance. key words: ontology population, syntactic feature extraction, latent semantic analysis, semantic web
Background: Renal dysfunction is associated with significantly lower apparent diffusion coefficient (ADC) values. There are several ADC-level cutoff points that indicate renal dysfunction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.