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Improving risk-stratification of Diabetes complications using temporal data mining.

L. Sacchi, A. Dagliati, D. Segagni, P. Leporati, L. Chiovato, and R. Bellazzi. EMBC, page 2131-2134. IEEE, (2015)

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Combining Naive Bayes Classifiers with Temporal Association Rules for Coronary Heart Disease Diagnosis.K. Orphanou, A. Dagliati, L. Sacchi, A. Stassopoulou, E. Keravnou, and R. Bellazzi. ICHI, page 81-92. IEEE Computer Society, (2016)A data gathering framework to collect Type 2 diabetes patients data.A. Dagliati, L. Sacchi, M. Bucalo, D. Segagni, K. Zarkogianni, A. Martinez-Millana, J. Cancela, F. Sambo, G. Fico, M. Barreira and 6 other author(s). BHI, page 244-247. IEEE, (2014)Template for preparation of papers for IEEE sponsored conferences & symposia.L. Sacchi, A. Dagliati, V. Tibollo, P. Leporati, P. Cata, C. Cerra, L. Chiovato, and R. Bellazzi. EMBC, page 2123-2126. IEEE, (2015)Mining Careflow Patterns in data warehouses of breast cancer patients.L. Sacchi, D. Segagni, A. Dagliati, A. Zambelli, and R. Bellazzi. AMIA, AMIA, (2013)Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective.A. Dagliati, V. Tibollo, L. Sacchi, A. Malovini, I. Limongelli, M. Gabetta, C. Napolitano, A. Mazzanti, P. Cata, L. Chiovato and 2 other author(s). Front. Digital Humanities, (2018)Inferring air quality maps from remotely sensed data to exploit georeferenced clinical onsets: The Pavia 2013 case.A. Marinoni, A. Dagliati, R. Bellazzi, and P. Gamba. IGARSS, page 3937-3940. IEEE, (2015)Temporal data mining and process mining techniques to identify cardiovascular risk-associated clinical pathways in Type 2 diabetes patients.A. Dagliati, L. Sacchi, C. Cerra, P. Leporati, P. Cata, L. Chiovato, J. Holmes, and R. Bellazzi. BHI, page 240-243. IEEE, (2014)Inferring Temporal Phenotypes with Topological Data Analysis and Pseudo Time-Series.A. Dagliati, N. Geifman, N. Peek, J. Holmes, L. Sacchi, S. Sajjadi, and A. Tucker. AIME, volume 11526 of Lecture Notes in Computer Science, page 399-409. Springer, (2019)Comparison of two temporal abstraction procedures: a case study in prediction from monitoring data.M. Verduijn, A. Dagliati, L. Sacchi, N. Peek, R. Bellazzi, E. de Jonge, and B. de Mol. AMIA, AMIA, (2005)Temporal abstractions to enrich Activity-Based Process Mining corpus with clinical time series.C. Fernández-Llatas, L. Sacchi, J. Benedí, A. Dagliati, V. Traver, and R. Bellazzi. BHI, page 785-788. IEEE, (2014)

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Improving risk-stratification of Diabetes complications using temporal data mining.

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Disambiguation of "Dagliati, Arianna"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Improving risk-stratification of Diabetes complications using temporal data mining.

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Improving risk-stratification of Diabetes complications using temporal data mining.