Cabitza F - Search Results

1

External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count.

Campagner A, Carobene A, Cabitza F. Campagner A, et al. Among authors: cabitza f. Health Inf Sci Syst. 2021 Oct 23;9(1):37. doi: 10.1007/s13755-021-00167-3. eCollection 2021 Dec. Health Inf Sci Syst. 2021. PMID: 34721844 Free PMC article.

2

Bridging the "last mile" gap between AI implementation and operation: "data awareness" that matters.

Cabitza F, Campagner A, Balsano C. Cabitza F, et al. Ann Transl Med. 2020 Apr;8(7):501. doi: 10.21037/atm.2020.03.63. Ann Transl Med. 2020. PMID: 32395545 Free PMC article. Review.

3

Assessment and prediction of spine surgery invasiveness with machine learning techniques.

Campagner A, Berjano P, Lamartina C, Langella F, Lombardi G, Cabitza F. Campagner A, et al. Among authors: cabitza f. Comput Biol Med. 2020 Jun;121:103796. doi: 10.1016/j.compbiomed.2020.103796. Epub 2020 May 16. Comput Biol Med. 2020. PMID: 32568677

4

H-Accuracy, an Alternative Metric to Assess Classification Models in Medicine.

Campagner A, Sconfienza L, Cabitza F. Campagner A, et al. Among authors: cabitza f. Stud Health Technol Inform. 2020 Jun 16;270:242-246. doi: 10.3233/SHTI200159. Stud Health Technol Inform. 2020. PMID: 32570383

5

Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground Truth.

Campagner A, Cabitza F. Campagner A, et al. Among authors: cabitza f. Stud Health Technol Inform. 2020 Jun 16;270:282-286. doi: 10.3233/SHTI200167. Stud Health Technol Inform. 2020. PMID: 32570391 Free article.

6

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.

Brinati D, Campagner A, Ferrari D, Locatelli M, Banfi G, Cabitza F. Brinati D, et al. Among authors: cabitza f. J Med Syst. 2020 Jul 1;44(8):135. doi: 10.1007/s10916-020-01597-4. J Med Syst. 2020. PMID: 32607737 Free PMC article.

7

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.

Seveso A, Campagner A, Ciucci D, Cabitza F. Seveso A, et al. Among authors: cabitza f. BMC Med Inform Decis Mak. 2020 Aug 20;20(Suppl 5):142. doi: 10.1186/s12911-020-01152-8. BMC Med Inform Decis Mak. 2020. PMID: 32819345 Free PMC article.

8

As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI.

Cabitza F, Campagner A, Sconfienza LM. Cabitza F, et al. BMC Med Inform Decis Mak. 2020 Sep 11;20(1):219. doi: 10.1186/s12911-020-01224-9. BMC Med Inform Decis Mak. 2020. PMID: 32917183 Free PMC article.

9

Routine blood tests as an active surveillance to monitor COVID-19 prevalence. A retrospective study.

Ferrari D, Cabitza F, Carobene A, Locatelli M. Ferrari D, et al. Among authors: cabitza f. Acta Biomed. 2020 Sep 7;91(3):e2020009. doi: 10.23750/abm.v91i3.10218. Acta Biomed. 2020. PMID: 32921707 Free PMC article.

10

Role of time-normalized laboratory findings in predicting COVID-19 outcome.

Ferrari D, Seveso A, Sabetta E, Ceriotti D, Carobene A, Banfi G, Locatelli M, Cabitza F. Ferrari D, et al. Among authors: cabitza f. Diagnosis (Berl). 2020 Nov 18;7(4):387-394. doi: 10.1515/dx-2020-0095. Diagnosis (Berl). 2020. PMID: 33035183 Free article.

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