Prognostic Factors/Neural Networks

Hillman RB, Kengeri SS, Waters DJ. Reevaluation of predictive factors for complete recovery in dogs with nonambulatory tetraparesis secondary to cervical disk herniation. J Am Anim Hosp Assoc. 2009; 45(4):155-63.

Waters DJ, Shen S, Xu H, Kengeri SS, Cooley DM, Chiang EC, Chen Y, Schlittler D, Oteham C, Combs GF Jr, Glickman LT, Morris JS, Bostwick DG. Noninvasive prediction of prostatic DNA damage by oxidative stress challenge of peripheral blood lymphocytes. Cancer Epidemiol Biomarkers Prev 2007; 16:1906-1910.

Bostwick DG, Adolfsson J, Burke HB, Damber JE, Huland H, Pavone-Macaluso M, Waters DJ. Epidemiology and statistical methods in prediction of patient outcome. Scand J Urol Nephrol Suppl 2005; (216):94-110.

Rodvold DM, McLeod DG, Brandt JM, Snow PB, Murphy GP. An introduction to artificial neural networks for physicians: taking the lid off the black box. Prostate 2001; 46(1):39-44.

Murphy GP, Snow P, Simmons SJ, Tjoa BA, Rogers MK, Brandt J, Healy CG, Bolton WE. The use of artifical neural networks in evaluating prognostic factors determining the response to dendritic cells pulsed with PSMA peptides in prostate cancer patients. Prostate 2000; 42(1):67-72.

Yarbro JW, Page DL, Fielding LP, Partridge EE, Murphy GP. American Joint Committee on Cancer Prognostic Factors Consensus Conference. Cancer 1999; 86(11):2436-2446.

Wajsman Z, Chu TM, Bross D, Saroff J, Murphy GP, Johnson DE, Scott, WW, Gibbons RP, Prout GR, Schmidt JD. Clinical significance of serum alkaline phosphatase isoenzyme levels in advanced prostatic carcinoma. J Urol 1977; 119(2):224-246.