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Prostate Calculator -  Recent abstracts and presentations

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Following are selected titles from abstracts and presentations given by the medical and computer modeling team behind this web site.

 Recent abstracts and presentations

Gamito, Crawford, Porter, O'Donnell, Bartsch, Horninger, Raben, & Tewari. A neural network model to predict prostate biopsy outcome using readily available clinical variables. American Society Clinical Oncologist 2002 Annual Meeting.

Porter, O'Donnell, Crawford, Gamito, Sentizimary, DeRosalia, Errejon, & Tewari. An artificial neural network to predict prostate biopsy outcome: a prospective study. American Society Clinical Oncologist 2002 Annual Meeting.

Tewari, Peabody, Bennett, Stricker, Crawford, Gamito, & Menon. Survival prediction tables in management of clinically localized prostate cancer: clinical utility of Tewari tables. American Urological Association 2002 Annual Meeting.

Tewari, Sonke, Verbeek, de la Rosette, Kiemeny, Gamito, Errejon, Crawford, O'Donnell, Burk, & Menon. Artificial neural network model to predict urinary bladder outlet obstruction in men with lower urinary tract symptoms. American Urological Association 2002 Annual Meeting.

Tewari, Peabody, Crawford, Gamito, Devine, Porter, & Menon. Impact of African American race on long term survival in patients with clinically localized prostate cancer. American Urological Association 2002 Annual Meeting.

Prediction of biopsy outcome from inverse PSA density calculated using the logarithm of PSA. Porter, Crawford, O'Donnell, Gamito, & Errejon. 12 International Prostate Cancer Update February 2002.

Predictive modeling techniques for estimating survival in patients with clinically localized prostate cancer. Tewari, Menon, Peabody, Crawford, Demers, Johnson, Farah, Stricker, Kim, Khil, Gamito & Divine. Podium Presentation. American Urological Association Annual Meeting.

ANN to predict risk of non-organ-confined disease and risk of lymph node spread in men with clinically localized prostate cancer. Crawford, Gamito, O'Donnell, Han, Partin, Tewari, Errejon, & Raben. Poster Presentation. American Urological Association Annual Meeting.

Artificial neural network model for predicting survival in men with advanced prostate cancer. O'Donnell, Errejon, Crawford, Kolvenbag, Carroll, Tewari, Batuello, & Gamito. American Society of Clinical Oncologists Annual Meeting.

Artificial neural network model to predict biochemical failure following radical prostatectomy. Porter, Crawford, O'Donnell, Gamito, Genega, & Tewari. American Society of Clinical Oncologists Annual Meeting.

Artificial neural network model to predict risk of non-organ-confined disease and risk of lymph node spread in men with clinically localized prostate cancer. Gamito, Crawford, O'Donnell, Han, Partin, Tewari, Errejon & Raben. Poster & Discussion. American Society of Clinical Oncologists Annual Meeting.

Batuello and Crawford. Use of artificial neural networks in predicting the presence of prostate cancer (update). 11th International Prostate Cancer Update, Vail, CO.

Gamito and Crawford. Getting more information from TRUS: Role of artificial neural networks. 11th International Prostate Cancer Update, Vail, CO.

Batuello, Gamito, Crawford, Partin, McLeod, Stock, & Stone. Artificial neural network to predict risk of lymph node spread in men with clinically localized prostate cancer and method to improve utility of ANN output. Poster Presentation. American Urological Association Annual Meeting.

Crawford et al. ANNs in predicting lymph node status and positive margins. European Association of Urology, Belgium.

Loch et al. Three dimensional prostate cancer imaging: Artificial neural network analysis (ANNA) of sub-visual transrectal ultrasound information. European Association of Urology, Belgium.

Gamito et al. Prediction of capsular penetration using an artificial neural network: A possible method for improving clinical staging in prostate cancer patients. American Society of Clinical Oncologists Annual Meeting.

Crawford et al. ANNs in predicting lymph node status and positive margins. 10th International Prostate Cancer Update, Vail, CO.

Gamito et al. Prediction of capsular penetration using an artificial neural network: A possible method for improving clinical staging in prostate cancer patients (update). 10th International Prostate Cancer Update, Vail, CO.

Crawford et. al. Use of artificial neural networks in predicting the presence of prostate cancer. Prostate Cancer in the New Millennium Scottsdale, AZ.

Dayhoff et al. ANNs: Opening the black box. All Surgeons Day, Washington, DC.

 


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Accessed on 12 December 2017.