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The common neurodegenerative pathologies underlying dementia are Alzheimer's disease (AD), Lewy body disease (LBD) and frontotemporal lobar degeneration (FTLD). Our aim was to identify patterns of atrophy unique to each of these diseases using antemortem structural MRI scans of pathologically confirmed dementia cases and build an MRI-based differential(More)
A precursor to many attacks on networks is often a reconnaissance operation, more commonly referred to as a scan. Despite the vast amount of attention focused on methods for scan detection, the state-of-the-art methods suffer from high rate of false alarms and low rate of scan detection. In this paper, we formalize the problem of scan detection as a data(More)
This chapter provides an overview of the Minnesota Intrusion Detection System (MINDS), which uses a suite of data mining based algorithms to address different aspects of cyber security. The various components of MINDS such as the scan detector, anomaly detector and the profiling module detect different types of attacks and intrusions on a computer network.(More)
— In this paper, we study the scanning activities towards a large campus network using a month-long netflow traffic trace. Based on the novel notion of " gray " IP space (namely, collection of IP addresses within our campus network that are not assigned to any " active " host during a certain period of time), we identify and extract potential outside(More)
Type-2 Diabetes Mellitus is a growing epidemic that often leads to severe complications. Effective preventive measures exist and identifying patients at high risk of diabetes is a major health-care need. The use of association rule mining (ARM) is advantageous, as it was specifically developed to identify associations between risk factors in an(More)
Associative classification is a predictive modeling technique that constructs a classifier based on class association rules (also known as predictive association rules; PARs). PARs are association rules where the consequence of the rule is a class label. Associative classification has gained substantial research attention because it successfully joins the(More)
Prediabetes is the most important risk factor for developing type-2 diabetes mellitus, an important and growing epidemic. Prediabetes is often associated with comorbidities including hypercholesterolemia. While statin drugs are indicated to treat hypercholesterolemia, recent reports suggest a possible increased risk of developing overt diabetes associated(More)
We describe our project that marries data mining together with Grid computing. Specifically, we focus on one data mining application-the Minnesota Intrusion Detection System (MINDS), which uses a suite of data mining based algorithms to address different aspects of cyber security including malicious activities such as denial-of-service (DoS) traffic, worms,(More)
In this paper, we propose a method, where the labeling of the data set is carried out in a semi-supervised manner with user-specified guarantees about the quality of the labeling. In our scheme, we assume that for each class, we have some heuristics available, each of which can identify instances of one particular class. The heuristics are assumed to have(More)