Artificial neural networks for prediction of lymph node status in breast cancer patients

Medical Hypotheses

Volumn 68, Issue 4, 2007, Pages 922-923

  Tez, Selda ^a   Yoldaş, Ömer ^b   Kiliç, Yusuf Alper ^c   Dizen, Hayrettin ^b   Tez, Mesut ^b  

^a 29 Mayis Hospital   (Turkey)

^b ANKARA TRAINING AND RESEARCH HOSPITAL   (Turkey)

^c HACETTEPE UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AXILLARY LYMPH NODE; BREAST CANCER; CANCER PATIENT; CANCER STAGING; FALSE NEGATIVE RESULT; HUMAN; LETTER; LYMPH NODE DISSECTION; MATHEMATICAL MODEL; METASTASIS; MORBIDITY; POSTOPERATIVE COMPLICATION; PREDICTION; PRIORITY JOURNAL; QUALITY OF LIFE; SENTINEL LYMPH NODE BIOPSY;

BREAST NEOPLASMS; FEMALE; HUMANS; LYMPH NODES; LYMPHATIC METASTASIS; NEURAL NETWORKS (COMPUTER); NEURONS; QUALITY OF LIFE; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENTINEL LYMPH NODE BIOPSY;

EID: 33846336698     PISSN: 03069877     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mehy.2006.09.028     Document Type: Letter

References (4)

1. Crippa F., Gerali A., Alessi A., Agresti R., and Bombardieri E. FDG-PET for axillary lymph node staging in primary breast cancer. Eur J Nucl Med Mol Imaging 31 Suppl. 1 (2004) S97-S102
2. Wilke L.G., McCall L.M., Posther K.E., Whitworth P.W., Reintgen D.S., Leitch A.M., et al. Surgical complications associated with sentinel lymph node biopsy: results from a prospective international cooperative group trial. Ann Surg Oncol 13 (2006) 491-500
3. Sargent D.J. Comparison of artificial neural networks with other statistical approaches - results from medical data sets. Cancer 91 8 Suppl. (2001) 1636-1642
4. Dvorchik I., Subotin M., Marsh W., McMichael J., and Fung J.J. Performance of multilayer feedforward neural networks to predict liver transplantation outcome. Meth Inf Med 35 (1996) 12-18