Genetically engineered neural networks for predicting prostate cancer progression after radical prostatectomy

Urology

Volumn 54, Issue 5, 1999, Pages 791-795

  Potter, Steven R ^a   Miller, M Craig ^b   Mangold, Leslie A ^a   Jones, Kerrie A ^a   Epstein, Jonathan I ^a,c   Veltri, Robert W ^b   Partin, Alan W ^a  

^a DEPARTMENT OF PATHOLOGY   (United States)

^b UroCor Incorporated   (United States)

^c JOHNS HOPKINS HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROSTATE SPECIFIC ANTIGEN;

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER GROWTH; DIAGNOSTIC VALUE; GENETIC ENGINEERING; HISTOPATHOLOGY; HUMAN; MAJOR CLINICAL STUDY; MALE; MORPHOMETRICS; PLOIDY; PRIORITY JOURNAL; PROGNOSIS; PROSTATE CANCER; PROSTATECTOMY;

ADULT; AGED; AGED, 80 AND OVER; DISEASE PROGRESSION; FOLLOW-UP STUDIES; GENETIC ENGINEERING; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; PROSTATECTOMY; PROSTATIC NEOPLASMS;

EID: 0032727778     PISSN: 00904295     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0090-4295(99)00328-3     Document Type: Article

References (15)

1. Merrill R.M., Brawley O.W. Prostate cancer incidence and mortality rates among white and black men. Epidemiology. 8:1997;126-131.
2. Kattan M.W., Eastham J.A., Stapleton A.M.F., et al. A preoperative nomogram for disease recurrence following radical prostatectomy for prostate cancer. J Natl Cancer Inst. 90:1998;766-771.
3. Partin A.W., Piantadosi S., Sanda M.G., et al. Selection of men at high risk for disease recurrence for experimental adjuvant therapy following radical prostatectomy. Urology. 45:1995;831-838.
4. Badalament R.A., Miller M.C., Peller P.A., et al. An algorithm for predicting non-organ confined prostate cancer using the results obtained from sextant core biopsies and prostate specific antigen level. J Urol. 156:1996;1375-1380.
5. D'Amico A.V., Whittington R., Malkowicz S.B., et al. A multivariate analysis of clinical and pathological factors that predict for prostate specific antigen failure after radical prostatectomy for prostate cancer. J Urol. 154:1995;131-138.
6. Veltri R.W., Miller M.C., Partin A.W., et al. Ability to predict biochemical progression using Gleason score and computer-generated quantitative nuclear grade derived from cancer cell nuclei. Urology. 48:1996;685-691.
7. Veltri R.W., O'Dowd G.J., Orozco R., et al. The role of biopsy pathology, quantitative nuclear morphometry, and biomarkers in the pre-op prediction of prostate cancer staging and prognosis. Semin Urol Oncol. 16:1998;106-117.
8. Partin A.W., Kattan M.W., Subong A.N.P., et al. Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer a multi-institutional update . JAMA. 277:1997;1445-1451.
9. Kattan M.W., Cowan M.E., Miles B.J. Computer modeling in urology. Urology. 47:1996;14-21.
10. Forrest S. Genetic algorithms principles of natural selection applied to computation . Science. 261:1993;872-878.
11. Snow P.B., Smith D.S., Catalona W.J. Artificial neural networks in the diagnosis and prognosis of prostate cancer a pilot study . J Urol. 152:1994;1923-1926.
12. Stotzka R., Manner R., Bartels P.H., et al. A hybrid neural and statistical classifier system for histopathologic grading of prostatic lesions. Anal Quant Cytol Histol. 17:1995;204-218.
13. Tewari A., Narayan P. Novel staging tool for localized prostate cancer a pilot study using genetic adaptive neural networks . J Urol. 160:1998;430-436.
14. Pound C.R., Partin A.W., Epstein J.I., et al. Prostate-specific antigen after anatomic radical retropubic prostatectomy patterns of recurrence and cancer control . Urol Clin North Am. 24:1997;395-406.
15. Bacus S.S., Bacus J.W., Bacus J.V., et al. Prostate adenocarcinoma an image analysis technique for DNA ploidy determination . Lab Med. 24:1994;225-231.