Bellazzi R - Search Results

1

Machine Learning Methods to Predict Diabetes Complications.

Dagliati A, Marini S, Sacchi L, Cogni G, Teliti M, Tibollo V, De Cata P, Chiovato L, Bellazzi R. Dagliati A, et al. Among authors: bellazzi r. J Diabetes Sci Technol. 2018 Mar;12(2):295-302. doi: 10.1177/1932296817706375. Epub 2017 May 12. J Diabetes Sci Technol. 2018. PMID: 28494618 Free PMC article.

2

Design, methods, and evaluation directions of a multi-access service for the management of diabetes mellitus patients.

Bellazzi R, Arcelloni M, Bensa G, Blankenfeld H, Brugués E, Carson E, Cobelli C, Cramp D, D'Annunzio G, De Cata P, De Leiva A, Deutsch T, Fratino P, Gazzaruso C, Garcìa A, Gergely T, Gómez E, Harvey F, Ferrari P, Hernando E, Boulos MK, Larizza C, Ludekke H, Maran A, Nucci G, Pennati C, Ramat S, Roudsari A, Rigla M, Stefanelli M. Bellazzi R, et al. Diabetes Technol Ther. 2003;5(4):621-9. doi: 10.1089/152091503322250640. Diabetes Technol Ther. 2003. PMID: 14511417

3

Management of patients with diabetes through information technology: tools for monitoring and control of the patients' metabolic behavior.

Bellazzi R, Arcelloni M, Ferrari P, Decata P, Hernando ME, García A, Gazzaruso C, Gómez EJ, Larizza C, Fratino P, Stefanelli M. Bellazzi R, et al. Diabetes Technol Ther. 2004 Oct;6(5):567-78. doi: 10.1089/dia.2004.6.567. Diabetes Technol Ther. 2004. PMID: 15628810

4

TA-clustering: cluster analysis of gene expression profiles through Temporal Abstractions.

Sacchi L, Bellazzi R, Larizza C, Magni P, Curk T, Petrovic U, Zupan B. Sacchi L, et al. Among authors: bellazzi r. Int J Med Inform. 2005 Aug;74(7-8):505-17. doi: 10.1016/j.ijmedinf.2005.03.014. Int J Med Inform. 2005. PMID: 15941669

5

Comparison of two temporal abstraction procedures: a case study in prediction from monitoring data.

Verduijn M, Dagliati A, Sacchi L, Peek N, Bellazzi R, de Jonge E, de Mol B. Verduijn M, et al. Among authors: bellazzi r. AMIA Annu Symp Proc. 2005;2005:749-53. AMIA Annu Symp Proc. 2005. PMID: 16779140 Free PMC article.

6

Inferring gene expression networks via static and dynamic data integration.

Ferrazzi F, Magni P, Sacchi L, Bellazzi R. Ferrazzi F, et al. Among authors: bellazzi r. Stud Health Technol Inform. 2006;124:119-24. Stud Health Technol Inform. 2006. PMID: 17108514

7

Precedence Temporal Networks to represent temporal relationships in gene expression data.

Sacchi L, Larizza C, Magni P, Bellazzi R. Sacchi L, et al. Among authors: bellazzi r. J Biomed Inform. 2007 Dec;40(6):761-74. doi: 10.1016/j.jbi.2007.06.003. Epub 2007 Jun 10. J Biomed Inform. 2007. PMID: 17644489 Free article.

8

Inferring gene regulatory networks by integrating static and dynamic data.

Ferrazzi F, Magni P, Sacchi L, Nuzzo A, Petrovic U, Bellazzi R. Ferrazzi F, et al. Among authors: bellazzi r. Int J Med Inform. 2007 Dec;76 Suppl 3:S462-75. doi: 10.1016/j.ijmedinf.2007.07.005. Epub 2007 Sep 6. Int J Med Inform. 2007. PMID: 17825607

9

TimeClust: a clustering tool for gene expression time series.

Magni P, Ferrazzi F, Sacchi L, Bellazzi R. Magni P, et al. Among authors: bellazzi r. Bioinformatics. 2008 Feb 1;24(3):430-2. doi: 10.1093/bioinformatics/btm605. Epub 2007 Dec 6. Bioinformatics. 2008. PMID: 18065427

10

Mining administrative and clinical diabetes data with temporal association rules.

Concaro S, Sacchi L, Cerra C, Bellazzi R. Concaro S, et al. Among authors: bellazzi r. Stud Health Technol Inform. 2009;150:574-8. Stud Health Technol Inform. 2009. PMID: 19745376

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