Naeem A. Mahoto

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0020-0255/$ see front matter 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ins.2013.06.046 ⇑ Corresponding author. Tel.: +39 0110907084; fax: +39 0110907099. E-mail addresses: elena.baralis@polito.it (E. Baralis), luca.cagliero@polito.it (L. Cagliero), naeem.mahoto@polito.it (N. Mahoto), alessandro.fio (A. Fiori). Elena Baralis , Luca(More)
The analysis of medical data is a challenging task for health care systems since a huge amount of interesting knowledge can be automatically mined to effectively support both physicians and health care organizations. This paper proposes a data analysis framework based on a multiple-level clustering technique to identify the examination pathways commonly(More)
Physicians and health care organizations always collect large amounts of data during patient care. These large and high-dimensional datasets are usually characterized by an inherent sparseness. Hence, analyzing these datasets to figure out interesting and hidden knowledge is a challenging task. This article proposes a new data mining framework based on(More)
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