Analysis of image cytometry data of fine needle aspirated cells of breast cancer patients: A comparison between logistic regression and artificial neural networks

Anticancer Research

Volumn 18, Issue 4 A, 1998, Pages 2723-2726

  Mat Sakim, H A ^a   Naguib, R N G ^a   Lakshmi, M S ^a   Wadehra, V ^b   Lennard, T W J ^a   Bhatavdekar, J ^c   Sherbet, G V ^a  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

^b ROYAL VICTORIA INFIRMARY   (United Kingdom)

^c GUJARAT CANCER AND RESEARCH INSTITUTE   (India)

Author keywords

Diagnosis; Histology; Lymph node; Multivariate analysis; Outcome prediction; Prognosis; Statistical analysis; Univariate analysis

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; ASPIRATION BIOPSY; AXILLARY LYMPH NODE; BREAST CANCER; CELL CYCLE S PHASE; FEMALE; HUMAN; HUMAN CELL; IMAGE CYTOMETRY; MAJOR CLINICAL STUDY; NEEDLE BIOPSY; PLOIDY; PRIORITY JOURNAL; REGRESSION ANALYSIS; TUMOR BIOPSY;

ANALYSIS OF VARIANCE; BIOPSY, NEEDLE; BREAST NEOPLASMS; FALSE NEGATIVE REACTIONS; FALSE POSITIVE REACTIONS; FEMALE; FLOW CYTOMETRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LYMPH NODES; LYMPHATIC METASTASIS; MULTIVARIATE ANALYSIS; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; PROGNOSIS; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 0031840542     PISSN: 02507005     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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