Chemotherapy Knowledge Base Management in the Era of Precision Oncology

Cancer medicine has grown increasingly complex in recent years with the advent of precision oncology and wide utilization of multidrug regimens. Representing this increasingly granular knowledge is a significant challenge. As users and managers of a freely available chemotherapy drug and regimen database, we describe the changes we have made to accommodate these challenges. These include the development of a domain ontology and increased granularity in the classification of cancer types on the website.

Construction productivity fuzzy knowledge base management system

Construction companies need a knowledge management system to collate, share and ultimately apply this knowledge in various projects. One of the most important elements that determine the time estimates of any construction project is productivity. Such projects have a predilection towards uncertainty and therefore require new generation of prediction models that utilizes available historical data. The research presented in this paper develops, using fuzzy approach, a knowledge base to analyze, extract and infer any underlying patterns of the data sets to predict the duration and productivity of a construction process. A six-step protocol has been followed to create this model: (i) determine which factors affect productivity; (ii) select those factors that are critical; (iii) build the fuzzy sets; (iv) generate the fuzzy rules and models; (v) develop the fuzzy knowledge base; and (vi) validate the efficacy and function of these models in predicting the productivity construction process. The fuzzy knowledge base was validated and verified using a case study and the results were satisfactory with 92.00% mean validity. In conclusion, the developed models and system demonstrated the ability of a knowledge base management to predict the patterns and productivity of different construction operations.