reviewed grants and contracts related to his work, including a grant from the US Government's Breast Cancer Program for the development of a comparative breast treatment model for breast cancer and a grant from the National Cancer Institute for the development of a cervical cancer risk model. He is a consultant to the National Cancer Institute and an Expert for the Centers for Medicare and Medicaid Services. He is Associate Professor of Medicine at the George Washington University School of Medicine. bcmhbb@gwumc.edu

Below is a selected list of Dr. Burke’s publications.

Book Chapters

Burke HB, Hutter RVP, Henson DE. Breast Carcinoma. In P Hermanek, MK Gospadoriwicz, DE

Henson, RVP Hutter, LH Sobin (eds), UICC Prognostic Factors in Cancer. Berlin:

Springer-Verlag, 1995, 165-176.

Burke HB, Rosen DB, Goodman PH. Comparing the prediction accuracy of artificial neural

networks and other statistical models for breast cancer survival. In G. Tesauro, D.S.

Touretzky, T.K. Leen (eds), Advances in Neural Information Processing Systems 7.

Cambridge, MA; MIT Press, 1995, 1063-67.

Burke HB. Statistical analysis of complex systems in biomedicine. In D. Fisher and H. Lenz

(eds), Learning from Data: Artificial Intelligence and Statistics V. New York: Springer-

Verlag, 1996, 251-258.

Burke HB. The importance of artificial neural networks and biomedicine. In P.E. Keller, S.

Hashem, L.J. Kangas, R.T. Kouzes (eds), Applications of Neural Networks in

Environment, Energy, and Health. Singapore; World Scientific Publishing Co., 1996,

145-153.

Burke HB. Integrating multiple clinical tests to increase predictive accuracy. In M. Hanausek, Z.

Walaszek (eds), Methods in Molecular Biology:, Vol. XX: Tumor Marker Protocols.

Totowa, N.J., Humana Press Inc., 1998, Chapter 1, 3 - 10.

Moul JW, Burke HB. Is the evidence for watchful waiting convincing: Argument for treatment

of clinically localized prostate cancer. In Greco C, Zelefsky M (eds), Radiotherapy of

Prostate Cancer. Australia: Harwood Academic; 2000, 49-54.

Journals

Burke HB, Henson DE. Criteria for prognostic factors and for an enhanced prognostic system.

Cancer 1993;72:3131-5.

Burke HB. Artificial neural networks for cancer research: outcome prediction. Sem Surg Onc

1994;10:73-79.

Burke HB. Increasing the power of surrogate endpoint biomarkers: the aggregation of predictive

factors. J Cell Biochem 1994;19S:278-82.

Bostwick DG, Burke HB, Wheeler TM, Chung LWK, Bookstein R, Pretlow TG, et al. The most

promising surrogate endpoint biomarkers for screening candidate chemopreventive

compounds for prostatic adenocarcinoma in short-term phase II clinical trials. J Cell

Biochem 1994;19S:283-89.

Burke HB, Goodman PH, Rosen DB, Henson DE, Weinstein JN, Harrell Jr. FE, Marks JR,

Winchester DP, Bostwick DG. Artificial neural networks improve the accuracy of cancer

survival prediction. Cancer 1997;79:857-62.

Burke HB. Henson DE. Histologic grade as a prognostic factor in breast carcinoma. Cancer

1997;80:1703-1705.

Burke HB, Hoang A, Iglehart JD, Marks JR. Predicting response to adjuvant and radiation

therapy in early stage breast cancer. Cancer 1998;82:874-7.

Burke HB. Applying artificial neural networks to clinical medicine. J Clin Ligand 1998;21:200-201.

Burke HB, Henson DE. Specimen banks for prognostic factor research. Arch Path Lab Med,

1998;122:871-874.

Burke HB, Henson DE. Evaluating prognostic factors. CME J Gyn Onc 1999;4:244-252.

Lundin M, Lundin J, Burke HB, Toikkanen S, Pylkkanen l, Joensuu H. Artificial neural networks

applied to survival prediction in breast cancer. Oncology 1999;57:281-286.

Seiter K, Feldman EJ, Halicka HD, Deptala A, Traganos F, Burke HB, Kancherla R, Ahmed T.

Clinical and laboratory evaluation of ATRA modulation of chemoterhapy in acute

myelogenous leukemia. Br J Haematol 2000;108:40-47.

Corda RS, Burke HB, Horowitz HW. Adherence with prescription medications among medical

professionals. J Southern Med 2000;93:585-589.

Bosze P, Bast RC, Berchuck A, Burke HB, Buller RE, Creasman WT, Dubeau L, Fox H, Geisler

HE, Geisler JP, Henson DE, Rustin GJ, Vermorken JB, Wells M, Wilbanks GD.

Consensus statements on prognostic factors in epithelial ovarian carcinoma. Eur J Gynaec

Oncol 2000;21:513-526.

Burke HB. Discovering clinically significant patterns in microarray generated data. Mol

Diagnosis, 2000;5:349-357.

Bostwick DG, Burke HB. Prediction of individual patient outcome in cancer: Comparison of

artificial neural networks and Kaplan-Meier methods. Cancer 2001;91:1643-46.

Burke HB. Challenges in dyslipidemia. Heart Disease 2002;4:141-6.

Burke HB. Neural networks and prediction of outcome in endocrine cancer. Endocrine-Related

Cancer, in press.

Bostwick DG, Burke HB, Djakiew D, et al. Human prostate cancer risk factors. Cancer, in press.

David G. Bostwick M.D., MBA, Medical Director, is a former Professor of Pathology and Urology at the Mayo Clinic. He is an international expert on prostate and bladder cancer (he is senior editor of the best selling textbook on Urologic Pathology). He has written more than 280 medical articles and 8 books on cancer, including the American Cancer Society's patient information book "Prostate Cancer- What Every Man and His Family Should Know". He is interested in patient information and prediction of outcome. He has collaborated with Dr. Burke for 8 years, during which time they have co-authored multiple medical papers and served together on two National Cancer Institute panels (Prognostic Factors Task Force and Tissue Bank Review Panel). Dr. Bostwick has received numerous clinical trial contracts, including several from the National Cancer Institute for Chemoprevention of Prostate Cancer. He currently operates an international pathology consultation company in Richmond Virginia and White Plains New York and is a Clinical Professor of Pathology at the University of Virginia at Charlottesville.