Combining expert knowledge and databases for risk management

Correctness, transparency and effectiveness are the principalattributes of knowledge derived from databases. In current data miningresearch there is a focus on efficiency improvement of algorithms forknowledge discovery. However important limitations of data mining canonly be dissolved by the integration of knowledge of experts in thefield, encoded in some accessible way, with knowledge derived formpatterns in the database. In this paper we will in particular discussmethods for combining expert knowledge and knowledge derived fromtransaction databases.The framework proposed is applicable to widevariety of risk management problems. We will illustrate the method ina case study on fraud discovery in an insurance company.risk management;datamining;knowledge discovery;knowledge based systems

'Nut en nog eens nut'; Over retoriek, mythes en rituelen in informatiesysteemonderzoek

Rede, in verkorte vorm uitgesproken bij de aanvaardig van het ambt van hoogleraar aan de Faculteit der Bedrijfskunde met als leeropdracht Bedrijfskunde, in het bijzonder Informatie Managementrelevance;rigor;academic research;applied research;information systems;relevantie;strengheid;akademisch onderzoek;toegepast onderzoek;informatie systemen

'Nut en nog eens nut'; Over retoriek, mythes en rituelen in informatiesysteemonderzoek

Rede, in verkorte vorm uitgesproken bij de aanvaardig van het ambt van hoogleraar aan de Faculteit der Bedrijfskunde met als leeropdracht Bedrijfskunde, in het bijzonder Informatie ManagementThere has been much debate in the management sciences in general and the field of information systems in particular over the tradeoffs between rigor and relevance. Since it is viewed as a tradeoff, most of those debating the is-sues take up position on one side or the other. On the one hand, mainly to gain acceptance as an academic discipline the management sciences have stressed rigor. On the other hand, the business community severely criticizes university education and research for its lack of relevance. In this paper an ap-proach is proposed to achieve both rigor and relevance. Part of the response suggested can be described as application driven theory development, mean-ing that relevance may be attained starting off with a concrete problem in the context of an actual problem situation. Theory becomes part of the equation when the approaches used are generalized and made publicly available for use by others and with sufficient rigor to allow for validation. Academia and business have their own specific role in such research processes

Combining expert knowledge and databases for risk management

Correctness, transparency and effectiveness are the principal attributes of knowledge derived from databases. In current data mining research there is a focus on efficiency improvement of algorithms for knowledge discovery. However important limitations of data mining can only be dissolved by the integration of knowledge of experts in the field, encoded in some accessible way, with knowledge derived form patterns in the database. In this paper we will in particular discuss methods for combining expert knowledge and knowledge derived from transaction databases.The framework proposed is applicable to wide variety of risk management problems. We will illustrate the method in a case study on fraud discovery in an insurance company

Has the Rate of CD4 Cell Count Decline before Initiation of Antiretroviral Therapy Changed over the Course of the Dutch HIV Epidemic among MSM?

Introduction:Studies suggest that the HIV-1 epidemic in the Netherlands may have become more virulent, leading to faster disease progression if untreated. Analysis of CD4 cell count decline before antiretroviral therapy (ART) initiation, a surrogate marker for disease progression, may be hampered by informative censoring as ART initiation is more likely with a steeper CD4 cell count decline.Methods:Development of CD4 cell count from 9 to 48 months after seroconversion was analyzed using a mixed-effects model and 2 models that jointly modeled CD4 cell counts and time to censoring event (start ART

Non-AIDS defining cancers in the D:A:D Study-time trends and predictors of survival : a cohort study

BACKGROUND:Non-AIDS defining cancers (NADC) are an important cause of morbidity and mortality in HIV-positive individuals. Using data from a large international cohort of HIV-positive individuals, we described the incidence of NADC from 2004-2010, and described subsequent mortality and predictors of these.METHODS:Individuals were followed from 1st January 2004/enrolment in study, until the earliest of a new NADC, 1st February 2010, death or six months after the patient's last visit. Incidence rates were estimated for each year of follow-up, overall and stratified by gender, age and mode of HIV acquisition. Cumulative risk of mortality following NADC diagnosis was summarised using Kaplan-Meier methods, with follow-up for these analyses from the date of NADC diagnosis until the patient's death, 1st February 2010 or 6 months after the patient's last visit. Factors associated with mortality following NADC diagnosis were identified using multivariable Cox proportional hazards regression.RESULTS:Over 176,775 person-years (PY), 880 (2.1%) patients developed a new NADC (incidence: 4.98/1000PY [95% confidence interval 4.65, 5.31]). Over a third of these patients (327, 37.2%) had died by 1st February 2010. Time trends for lung cancer, anal cancer and Hodgkin's lymphoma were broadly consistent. Kaplan-Meier cumulative mortality estimates at 1, 3 and 5 years after NADC diagnosis were 28.2% [95% CI 25.1-31.2], 42.0% [38.2-45.8] and 47.3% [42.4-52.2], respectively. Significant predictors of poorer survival after diagnosis of NADC were lung cancer (compared to other cancer types), male gender, non-white ethnicity, and smoking status. Later year of diagnosis and higher CD4 count at NADC diagnosis were associated with improved survival. The incidence of NADC remained stable over the period 2004-2010 in this large observational cohort.CONCLUSIONS:The prognosis after diagnosis of NADC, in particular lung cancer and disseminated cancer, is poor but has improved somewhat over time. Modifiable risk factors, such as smoking and low CD4 counts, were associated with mortality following a diagnosis of NADC