Andriy I. Bandos, PhD

Dr. Andriy Bandos’s primary research interest is the design and analysis of studies of accuracy of classification and prediction. Major focus of his collaborative work has been in design and analysis of multi-reader retrospective as well as prospective studies of diagnostic technologies for medical imaging. His current methodological research includes statistical evaluation of detection and classification performance, ROC analysis, design and analysis of multi-reader (MRMC) studies, free-response ROC (FROC) methodology, nonparametric methods and resampling approaches in statistics. Most of methodological developments stemmed from the collaborative work and aimed to address questions frequently arising in practice. 

 

2005 | University of Pittsburgh, Pittsburgh, PA| Ph.D. Biostatistics

2000 | V.N. Karazin Kharkiv National University, Ukraine | MS (Specialist) Mathematics 

BIOST 2043 (Introduction to Statistical Theory I)

BIOST 2044 (Introduction to Statistical Theory II)

BIOST 2056 (Introduction to Diagnostic Test Evaluation and ROC Analysis)

BIOST 2038 (Foundations of Statistical Theory)

Skaane P, Bandos AI, Niklason LT, Sebuødegård S, Østerås BH, Gullien R, Gur D, Hofvind S. (2019) Digital Mammography versus Digital Mammography Plus Tomosynthesis in Breast Cancer Screening: the Olso Tomosynthesis Screening Trial. Radiology. 291(1): 23-30.

 

Bandos, A.I., Obuchowski, N.A. (2018). Evaluation of Diagnostic Accuracy in Free-Response Detection-Localization Tasks Using ROC tools. Statistical Methods in Medical Research. In Press.

 

Ma, H., Bandos, A.I., Gur, D. (2018). Informativeness of Diagnostic Marker Values and the Impact of Data Grouping. Computational Statistics and Data Analysis. 117: 76-89.

 

Oligane, H.C., Berg, W.A., Bandos, A.I., Chen, S.S., Sohrabi, S., Anello ,M., Zuley, M.L. (2018). Grouped Amorphous Calcifications on Mammography: Frequently Atypical but Rarely Associated with Aggressive Malignancy. Radiology. 288(3): 671-679.

 

Bandos, A.I., Guo, B., Gur, D. (2017). Jackknife variance of the partial area under the empirical receiver operating characteristic curve. Statistical Methods in Medical Research. 26(2):528-541

 

Bandos AI, Guo B, Gur D. (2017). Estimating the Area Under ROC Curve when the Fitted Binormal Curves Demonstrate Improper Shape. Academic Radiology. 24(2): 209-19.

 

Berg, W. A., Bandos, A.I., Mendelson, E.B., Lehrer, D., Jong, R.A., Pisano, E.D. (2016) Ultrasound as the primary screening test for breast cancer: analysis from ACRIN 6666. Journal of the National Cancer Institute 108(4): 1-8

 

Ma, H., Bandos, A. I.,Gur, D. (2015). On the use of partial area under the ROC curve for comparison of two diagnostic tests. Biometrical Journal. 57(2): 304-20

 

Callahan, M. J., Kleinman, P. L., Strauss, K. J., Bandos, A.I., Taylor, G. A., Tsai, A., & Kleinman, P. K. (2015). Pediatric CT dose reduction for suspected appendicitis: a practice quality improvement project using artificial Gaussian noise--part 1, computer simulations. American Journal of Roentgenology. 204(1): 86-94

 

Aggarwal, R., Bandos, A.I., Reed, A.M., Ascherman, D.P., Barohn, R.J., Feldman, B.M., Miller, F.W., Rider, L.G., Harris-Love, M.O., Levesque, M.C.; the RIM Study Group, Oddis, C.V. (2014). Predictors of clinical improvement in rituximab-treated refractory adult and juvenile dermatomyositis and adult polymyositis. Arthritis and Rheumatism. 66: 740-749

 

Bandos, A.I., Rockette, H.E., Gur, D. (2013). Subject-centered free-response ROC (FROC) analysis. Medical Physics. 40 (5):051706

 

Skaane, P., Bandos, A.I., Gullien, R., Eben, E.B., Ekseth, U., Haakenaasen, U., Izadi, M., Jebsen, I.N., Jahr, G., Krager, M., Hofvind, S. (2013). Prospective trial comparing full-field digital mammography (FFDM) versus combined FFDM and tomosynthesis in a population-based screening programme using independent double reading with arbitration. European Radiology. 23(8):2061-2071

 

Ma, H., Bandos, A.I., Rockette, H.E., Gur, D. (2013). On use of partial area under the ROC curve for evaluation of diagnostic performance. Statistics in Medicine. 32(20): 3449-3458

 

Zuley, M.L., Bandos A.I., Ganott, M.A., Sumkin, J.H., Kelly, A.E., Catullo, V.J., Rathfon, G.Y., Lu, A.H., Gur, D. (2013). Digital breast tomosynthesis versus supplemental diagnostic mammographic views for evaluation of noncalcified breast lesions. Radiology. 266 (1):89-95

 

Zou KH, Liu A, Bandos AI, Ohno-Machado L, Rockette HE. (2011). Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. (1st ed.). CRC press, Taylor & Francis Group. (Chapters 2,7,8)

 

Bandos, A.I., Rockette, H., Gur, D. (2010). Use of Likelihood Ratios for Comparison of Binary Diagnostic Tests: Underlying ROC Curves. Medical Physics. 37 (11): 5821-5830

 

Gur, D., Abrams, G.S., Chough, D.M., Ganott, M.A., Hakim, C.M., Perrin, R.L., Rathfon, G.Y., Sumkin, J.H., Zuley, M.L., Bandos, A.I. (2009). Digital Breast Tomosynthesis- An Observer Performance Study. American Journal of Roentgenology. 193(2): 586-59

 

Bandos, A.I., Rockette, H.E., Song, T., Gur, D. (2009). Area under the free-response ROC curve (FROC) and a related summary index. Biometrics. 65:247-256

 

Gallas, B., Bandos, A.I., Samuelson, F., Wagner, R. (2009). A framework for random-effects ROC analysis: biases with the bootstrap and other variance estimators. Communications in Statistics, Theory and Methods. 38(15): 2586-2603

 

Bandos, A.I., Rockette H.E., Gur D. (2007). Exact bootstrap variances of the area under the ROC curve. Communications in Statistics – Theory & Methods. 36(13): 2443 – 2461

 

Bandos, A.I., Rockette, H.E., Gur, D. (2005). A permutation test sensitive to differences in areas for comparing ROC curves from a paired design. Statistics in Medicine. 24(18): 2873-2893