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Full-Text Articles in Computer Sciences
Mining Of Primary Healthcare Patient Data With Selective Multimorbid Diseases, Annette Megerdichian Azad
Mining Of Primary Healthcare Patient Data With Selective Multimorbid Diseases, Annette Megerdichian Azad
Electronic Thesis and Dissertation Repository
Despite a large volume of research on the prognosis, diagnosis and overall burden of multimorbidity, very little is known about socio-demographic characteristics of multimorbid patients. This thesis aims to analyze the socio-demographic characteristics of patients with multiple chronic conditions (multimorbidity), focusing on patient groups sharing the same combination of diseases. Several methods were explored to analyze the co-occurrence of multiple chronic diseases as well as the associations between socio-demographics and chronic conditions. These methods include disease pair distributions over gender, age groups and income level quintiles, Multimorbidity Coefficients for measuring the concurrence of disease pairs and triples, and k-modes clustering …
Clustering-Based Personalization, Seyed Nima Mirbakhsh
Clustering-Based Personalization, Seyed Nima Mirbakhsh
Electronic Thesis and Dissertation Repository
Recommendation systems have been the most emerging technology in the last decade as one of the key parts in e-commerce ecosystem. Businesses offer a wide variety of items and contents through different channels such as Internet, Smart TVs, Digital Screens, etc. The number of these items sometimes goes over millions for some businesses. Therefore, users can have trouble finding the products that they are looking for. Recommendation systems address this problem by providing powerful methods which enable users to filter through large information and product space based on their preferences. Moreover, users have different preferences. Thus, businesses can employ recommendation …
Localizing State-Dependent Faults Using Associated Sequence Mining, Shaimaa Ali
Localizing State-Dependent Faults Using Associated Sequence Mining, Shaimaa Ali
Electronic Thesis and Dissertation Repository
In this thesis we developed a new fault localization process to localize faults in object oriented software. The process is built upon the "Encapsulation'' principle and aims to locate state-dependent discrepancies in the software's behavior. We experimented with the proposed process on 50 seeded faults in 8 subject programs, and were able to locate the faulty class in 100% of the cases when objects with constant states were taken into consideration, while we missed 24% percent of the faults when these objects were not considered. We also developed a customized data mining technique "Associated sequence mining'' to be used in …