Improvement of breast cancer relapse prediction in high risk intervals using artificial neural networks

Breast Cancer Research and Treatment

Volumn 94, Issue 3, 2005, Pages 265-272

  Jerez, J M ^a   Franco, L ^a,b   Alba, E ^c   Llombart Cussac, A ^d   Lluch, A ^e   Ribelles, N ^c   Munarriz B ^f   Martin M ^g  

^a UNIVERSITY OF MÁLAGA   (Spain)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c HOSPITAL UNIVERSITARIO VIRGEN DE LA VICTORIA   (Spain)

^d INSTITUTO VALENCIANO DE ONCOLOGÍA   (Spain)

^e HOSPITAL GENERAL UNIVERSITARIO DE VALENCIA   (Spain)

^f HOSPITAL UNIVERSITARIO LA FE   (Spain)

^g HOSPITAL CLÍNICO SAN CARLOS   (Spain)

Author keywords

Breast cancer prognosis; Cox proportional hazard model; High peaks of relapse; Neural networks; Survival analysis

Indexed keywords

ACCURACY; ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST CANCER; CANCER RELAPSE; CONTROLLED STUDY; FEMALE; FOLLOW UP; HUMAN; LYMPH NODE; MAJOR CLINICAL STUDY; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; RISK ASSESSMENT; SPAIN; STATISTICAL ANALYSIS; STATISTICAL SIGNIFICANCE; SURVIVAL; TUMOR VOLUME;

ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; BREAST NEOPLASMS; FEMALE; FORECASTING; HUMANS; LYMPHATIC METASTASIS; MIDDLE AGED; NEOPLASM STAGING; NEURAL NETWORKS (COMPUTER); PROGNOSIS; PROPORTIONAL HAZARDS MODELS; RISK ASSESSMENT;

EID: 27944509655     PISSN: 01676806     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10549-005-9013-y     Document Type: Article

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