Carobene A - Search Results

1

Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?

Padoan A, Cadamuro J, Frans G, Cabitza F, Tolios A, De Bruyne S, van Doorn W, Elias J, Debeljak Z, Perez SM, Özdemir H, Carobene A. Padoan A, et al. Among authors: carobene a. Clin Chem Lab Med. 2024 Oct 7. doi: 10.1515/cclm-2024-0971. Online ahead of print. Clin Chem Lab Med. 2024. PMID: 39367764 Free article.

2

Prevalence of metabolic syndrome among patients with schizophrenia in Ethiopia.

Challa F, Getahun T, Sileshi M, Geto Z, Kelkile TS, Gurmessa S, Medhin G, Mesfin M, Alemayehu M, Shumet T, Mulugeta A, Bekele D, Borba CPC, Oppenheim CE, Henderson DC, Fekadu A, Carobene A, Teferra S. Challa F, et al. Among authors: carobene a. BMC Psychiatry. 2021 Dec 11;21(1):620. doi: 10.1186/s12888-021-03631-2. BMC Psychiatry. 2021. PMID: 34895175 Free PMC article.

3

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: carobene a. Acta Biomed. 2020 Sep 7;91(3):e2020009. doi: 10.23750/abm.v91i3.10218. Acta Biomed. 2020. PMID: 32921707 Free PMC article.

4

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: carobene a. Diagnosis (Berl). 2020 Nov 18;7(4):387-394. doi: 10.1515/dx-2020-0095. Diagnosis (Berl). 2020. PMID: 33035183 Free article.

5

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests.

Cabitza F, Campagner A, Ferrari D, Di Resta C, Ceriotti D, Sabetta E, Colombini A, De Vecchi E, Banfi G, Locatelli M, Carobene A. Cabitza F, et al. Among authors: carobene a. Clin Chem Lab Med. 2020 Oct 21;59(2):421-431. doi: 10.1515/cclm-2020-1294. Clin Chem Lab Med. 2020. PMID: 33079698 Free article.

6

The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands.

Carobene A, Campagner A, Uccheddu C, Banfi G, Vidali M, Cabitza F. Carobene A, et al. Clin Chem Lab Med. 2021 Aug 2;60(4):556-568. doi: 10.1515/cclm-2021-0599. Print 2022 Mar 28. Clin Chem Lab Med. 2021. PMID: 34333884 Free article.

7

The importance of being external. methodological insights for the external validation of machine learning models in medicine.

Cabitza F, Campagner A, Soares F, García de Guadiana-Romualdo L, Challa F, Sulejmani A, Seghezzi M, Carobene A. Cabitza F, et al. Among authors: carobene a. Comput Methods Programs Biomed. 2021 Sep;208:106288. doi: 10.1016/j.cmpb.2021.106288. Epub 2021 Jul 22. Comput Methods Programs Biomed. 2021. PMID: 34352688 Free article.

8

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: carobene a. 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.

9

A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients.

Famiglini L, Campagner A, Carobene A, Cabitza F. Famiglini L, et al. Among authors: carobene a. Med Biol Eng Comput. 2022 Mar 30:1-13. doi: 10.1007/s11517-022-02543-x. Online ahead of print. Med Biol Eng Comput. 2022. PMID: 35353302 Free PMC article. Review.

10

How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory data.

Carobene A, Milella F, Famiglini L, Cabitza F. Carobene A, et al. Clin Chem Lab Med. 2022 May 5;60(12):1887-1901. doi: 10.1515/cclm-2022-0182. Print 2022 Nov 25. Clin Chem Lab Med. 2022. PMID: 35508417 Free article. Review.

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