Lara Lusa

  • LUSA, Lara, BUKOVŠEK, David. Providing patients visiting emergency departments with useful information using public real time data : a case study based on Italian data. Journal of evaluation in clinical practice, ISSN 1356-1294, 2018, (doi).
  • SEM, Vilma, KOLAR, Jana, LUSA, Lara. Artificially generated near-infrared spectral data for classification purposes. Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439. Jan. 2018, vol. 172, str. 100-108, (doi).
  • PUHR, Rainer, HEINZE, Georg, LUSA, Lara, GEROLDINGER, Angelika. Firth's logistic regression with rare events : accurate effect estimates and predictions?. Statistics in medicine, ISSN 0277-6715, Jun. 2017, vol. 36, iss. 14, str. 2302-2317. (doi) .
  • BLAGUS, Rok, LUSA, Lara. Gradient boosting for high-dimensional prediction of rare events. Computational statistics & data analysis, ISSN 0167-9473, Sep. 2017, vol. 113, str.19-37, (doi).
  • AHLIN, Crt, STUPICA, Dasa, STRLE, Franc, LUSA, Lara. medplot: A Web Application for Dynamic Summary and Analysis of Longitudinal Medical Data Based on R. PLoS One, 2015, (doi).
  • ŠUŠTAR, Vilma, KOLAR, Jana, LUSA, Lara, LEARNER, Tom, SCHILLING, Michael, RIVENC, Rachel, KHANJIAN, Herant, KOLEŠA, Dušan. Identification of historical polymers using Near-infrared spectroscopy. Polymer degradation and stability, ISSN 0141-3910, 2014, vol. 107, september, str. 341-347. 
  • BLAGUS, Rok, LUSA, Lara. SMOTE for high-dimensional class-imbalanced data. BMC bioinformatics, ISSN 1471-2105, 2013, vol. 14, str. [1-19], 106. http://www.biomedcentral.com/1471-2105/14/106/abstract, (doi) .
  • BLAGUS, Rok, LUSA, Lara. Improved shrunken centroid classifiers for high-dimensional class-imbalanced data. BMC bioinformatics, ISSN 1471-2105, 2013, vol. 14, str. [1-27], 64. http://www.biomedcentral.com/1471-2105/14/64/abstract, (doi).
  • GALSWORTHY, Michael J., HRISTOVSKI, Dimitar, LUSA, Lara, ERNST, Kelly, et al. Academic output of 9 years of EU investment into health research. The Lancet, ISSN 0140-6736. [Print ed.], 2012, letn. 380, št. 9846, str. 971-972. (doi) .
  • BLAGUS, Rok, LUSA, Lara. Impact of class-imbalance on multi-class high-dimensional class prediction. Metodološki zvezki, ISSN 1854-0023. [Tiskana izd.], 2012, vol. 9, no. 1, str. 25-45, ilustr. Link to the paper .
  • BLAGUS, Rok, LUSA, Lara. Class prediction for high-dimensional class-imbalanced data. BMC bioinformatics, 2010, letn. 11, str. 523 (1-27), (doi).
  • LUSA, Lara, KORN, Edward Lee, MCSHANE, Lisa M. A class comparison method with filtering-enhanced variable selection for high-dimensional data sets. Stat Med, 2008, letn. 27, št. 28, str. 5834-5849
  • GREGORI, Dario, LUSA, Lara, ROSATO, Rosalba, SILVESTRI, Luciano. Evaluating effectiveness of preoperative testing procedure: some notes on modeling strategies in multi-centre surveys. J. eval. clin. pract. (Print), 2008, letn. 14, str. 11-18.
  • LUSA, Lara, MCSHANE, Lisa M., REID, James F., DE CECCO, Loris, AMBROGI, Federico, BIGANZOLI, Elia, GARIBOLDI, Manuela, PIEROTTI, Marco A. Challenges in projecting clustering results across gene expression-profiling datasets. J. Natl. Cancer Inst., 2007, letn. 99, št. 22, str. 1715-1723.
  • LUSA, Lara, MCSHANE, Lisa M., RADMACHER, Michael D, SHIH, Joanna H., WRIGHT, George W, SIMON, Richard. Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray data. Stat Med, 2007, letn. 26, št. 5, str. 1102-1113.
  • LUSA, Lara, MICELI, Rosalba, MARIANI, Luigi. Estimation of predictive accuracy in survival analysis using R and S-PLUS. Comput. methods programs biomed. [Print ed.], 2007, letn. 87, št. 2, str. 132-137.
  • LUSA, Lara, CAPPELLETTI, V, GARIBOLDI, Manuela, FERRARIO, Cristina, DE CECCO, Loris, REID, James F., TOFFANIN, S, GALLUS, Giuseppe, MCSHANE, Lisa M., DAIDONE, Maria Grazia, PIEROTTI, Marco A. Questioning the utility of pooling samples in microarray experiments with cell lines. Int. j. biol. markers, 2006, letn. 21, št. 2, str. 67-73.
  • REID, James F., LUSA, Lara, DE CECCO, Loris, CORADINI, Danila, VENERONI, Silvia, DAIDONE, Maria Grazia, GARIBOLDI, Manuela, PIEROTTI, Marco A. Limits of predictive models using microarray data for breast cancer clinical treatment outcome. J. Natl. Cancer Inst., 2005, letn. 97, št. 12, str. 927-930.
  • MICELI, Rosalba, LUSA, Lara, MARIANI, Luigi. Revising a prognostic index developed for classification purposes: an application to gastric cancer data. J. appl. stat., 2004, letn. 31, št. 7, str. 817-830.

Na kratko o IBMI

Inštitut za biostatistiko in medicinsko informatiko (IBMI), prej Inštitut za biomedicinsko informatiko (torej tudi IBMI), je Medicinska fakulteta ustanovila leta 1973 kot izraz potrebe po izvajanju in usklajevanju del, vezanih na analizo podatkov in posredovanje informacij. Program dela in razvoja se je skozi čas prilagajal predvsem spremembam pri financiranju in tehnološkemu napredku, vendar so temeljne smernice ostale enake: inštitut se predvsem posveča dejavnostim, ki so pomembne za raziskovalno delo v medicini. Te pa lahko razdelimo na:

Kontakt

Inštitut za biostatistiko in medicinsko informatiko
Medicinska fakulteta
Univerza v Ljubljani
Vrazov trg 2, 1000 Ljubljana, Slovenija

tel: (01) 543-77-70
fax: (01) 543-77-71
email: ibmi (at) mf.uni-lj.si