Multiple neural network response variability as a predictor of neural network accuracy for chromosome recognition

Biomedical Sciences Instrumentation

Volumn 32, Issue , 1996, Pages 31-37

  Leon, Mauricio A ^a   Gader, Paul ^a   Keller, James ^a  

^a UNIVERSITY OF MISSOURI   (United States)

Author keywords

Automated karyotyping; Chromosome classification; Neural networks

Indexed keywords

BACKPROPAGATION; CELLS; CHROMOSOMES; GENETIC ENGINEERING; LEARNING SYSTEMS; MEDICAL COMPUTING; PROBLEM SOLVING;

CHROMOSOME CLASSIFICATION; HUMAN CELL; MULTIPLE NEURAL NETWORK;

NEURAL NETWORKS;

ACCURACY; ARTIFICIAL NEURAL NETWORK; AUTOANALYSIS; CELL DIVISION; CHROMOSOME ANALYSIS; CLASSIFICATION; COMPUTER ANALYSIS; CONFERENCE PAPER; DATA BASE; DENMARK; ERROR; HUMAN; HUMAN CELL; KARYOTYPING; PROBLEM SOLVING; SCORING SYSTEM;

HUMANS; KARYOTYPING; NEURAL NETWORKS (COMPUTER);

EID: 0029873606     PISSN: 00678856     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (5)

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3. Sweeney WP Jr. Musavi MT. Guidi JN. Classification of chromosomes using a probabilistic neural network. Cytometry. 16(1):17-24, 1994.
4. Graham J. Errington P. Jennings A. A neural network chromosome classifier. Journal of Radiation Research. 33 Suppl:250-7, 1992.
5. Lundsteen C. Philip J. Granum E. Quantitative analysis of 6985 digitized trypsin G-banded human metaphase. Clinical Genetics. 18(5):355-70, 1980.