Intelligent data analysis - support for development of SMEs sector

The paper studies possibilities of intelligent data analysis application for discovering knowledge hidden in small and medium-sized enterprises’ (SMEs) data, on the territory of the province of Vojvodina. The knowledge revealed by intelligent analysis, and not accessible by any other means, could be the valuable starting point for working out of proactive and preventive actions for the development of the SMEs sector.Intelligent data analysis, CRISP-DM, clustering, small and medium enterprises., Research and Development/Tech Change/Emerging Technologies, C8, L2,

Transforming Web Data Into Knowledge - Implications for Management

Much of one’s online behavior, including browsing, shopping, posting, is recorded in databases on companies’ computers on a daily basis. Those data sets are referred to as web data. The patterns which are the indicators of one’s interests, habits, preferences or behaviors are stored within those data. More useful than an individual indicator is when a company records data on all its users and when it gains an insight into their habits and tendencies. Detecting and interpreting such patterns can help managers to make informed decisions and serve their customers better. Utilizing data mining with respect to web data is said to turn them into web knowledge. The research study conducted in this paper demonstrates how data mining methods and models can be applied to the web-based forms of data, on the one hand, and what the implications of uncovering patterns in web content, the structure and their usage are for management

Intelligent data analysis - support for development of SMEs sector

The paper studies possibilities of intelligent data analysis application for discovering knowledge hidden in small and medium-sized enterprises’ (SMEs) data, on the territory of the province of Vojvodina. The knowledge revealed by intelligent analysis, and not accessible by any other means, could be the valuable starting point for working out of proactive and preventive actions for the development of the SMEs sector

Online Journal of Applied Knowledge Management Improving the interestingness of web usage association rules containing common web site menu items

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Ofatumumab versus Teriflunomide in Multiple Sclerosis

BACKGROUND: Ofatumumab, a subcutaneous anti-CD20 monoclonal antibody, selectively depletes B cells. Teriflunomide, an oral inhibitor of pyrimidine synthesis, reduces T-cell and B-cell activation. The relative effects of these two drugs in patients with multiple sclerosis are not known. METHODS: In two double-blind, double-dummy, phase 3 trials, we randomly assigned patients with relapsing multiple sclerosis to receive subcutaneous ofatumumab (20 mg every 4 weeks after 20-mg loading doses at days 1, 7, and 14) or oral teriflunomide (14 mg daily) for up to 30 months. The primary end point was the annualized relapse rate. Secondary end points included disability worsening confirmed at 3 months or 6 months, disability improvement confirmed at 6 months, the number of gadolinium-enhancing lesions per T1-weighted magnetic resonance imaging (MRI) scan, the annualized rate of new or enlarging lesions on T2-weighted MRI, serum neurofilament light chain levels at month 3, and change in brain volume. RESULTS: Overall, 946 patients were assigned to receive ofatumumab and 936 to receive teriflunomide; the median follow-up was 1.6 years. The annualized relapse rates in the ofatumumab and teriflunomide groups were 0.11 and 0.22, respectively, in trial 1 (difference, -0.11; 95% confidence interval [CI], -0.16 to -0.06; P<0.001) and 0.10 and 0.25 in trial 2 (difference, -0.15; 95% CI, -0.20 to -0.09; P<0.001). In the pooled trials, the percentage of patients with disability worsening confirmed at 3 months was 10.9% with ofatumumab and 15.0% with teriflunomide (hazard ratio, 0.66; P = 0.002); the percentage with disability worsening confirmed at 6 months was 8.1% and 12.0%, respectively (hazard ratio, 0.68; P = 0.01); and the percentage with disability improvement confirmed at 6 months was 11.0% and 8.1% (hazard ratio, 1.35; P = 0.09). The number of gadolinium-enhancing lesions per T1-weighted MRI scan, the annualized rate of lesions on T2-weighted MRI, and serum neurofilament light chain levels, but not the change in brain volume, were in the same direction as the primary end point. Injection-related reactions occurred in 20.2% in the ofatumumab group and in 15.0% in the teriflunomide group (placebo injections). Serious infections occurred in 2.5% and 1.8% of the patients in the respective groups. CONCLUSIONS: Among patients with multiple sclerosis, ofatumumab was associated with lower annualized relapse rates than teriflunomide. (Funded by Novartis; ASCLEPIOS I and II ClinicalTrials.gov numbers, NCT02792218 and NCT02792231.)