Title :
Validation of a large medical database
Author :
Rovetta, Guido ; Monteforte, Patrizia ; Bianchi, Gerolamo ; Rovetta, Stefano ; Zunino, Rodolfo
Author_Institution :
Fac. of Eng, Genova Univ., Italy
Abstract :
Complex clinical problems involving huge experimental evidence require a preliminary validation of observed data. This may avoid biasing due to incorrect sampling and clarify the sample distribution by showing data-inherent regularities. The paper describes the application of unsupervised models of neural networks to the analysis of a very large set of clinical records for the study of osteoporosis. The main result obtained lies in showing the overall uniformity of the data distribution, which indicates a correct unbiased sampling of the considered population
Keywords :
data integrity; medical information systems; neural nets; probability; unsupervised learning; very large databases; biasing; clinical problems; clinical records analysis; data distribution uniformity; data-inherent regularities; database validation; experimental evidence; incorrect sampling; large medical database; neural networks; observed data validation; osteoporosis; sample distribution; unbiased sampling; unsupervised models; Biomedical engineering; Costs; Data engineering; Data mining; Databases; Medical diagnostic imaging; Neural networks; Osteoporosis; Pattern recognition; Sampling methods;
Conference_Titel :
Computer-Based Medical Systems, 1995., Proceedings of the Eighth IEEE Symposium on
Conference_Location :
Lubbock, TX
Print_ISBN :
0-8186-7117-3
DOI :
10.1109/CBMS.1995.465447
