Pitfalls in the Use of DNA Microarray Data for Diagnostic and Prognostic Classification
β Scribed by Simon, R.; Radmacher, M. D.; Dobbin, K.; McShane, L. M.
- Book ID
- 118036183
- Publisher
- Oxford University Press
- Year
- 2003
- Tongue
- English
- Weight
- 69 KB
- Volume
- 95
- Category
- Article
- ISSN
- 0027-8874
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Using a measure of how differentially expressed a gene is in two biochemically/phenotypically different conditions, we can rank all genes in a microarray dataset. We have shown that the falling-off of this measure (normalized maximum likelihood in a classification model such as logistic regression)
The application of arti"cial neural networks (ANNs) for prognostic and diagnostic classi"cation in clinical medicine has become very popular. In particular, feed-forward neural networks have been used extensively, often accompanied by exaggerated statements of their potential. In this paper, the ess
In the fight against cervical malignancy and its precursors, several adjuvant diagnostic methods have been proposed to increase the accuracy of cytologic and histologic diagnoses. Because chromosomal aneuploidy has been accepted as an early key event in tumorigenesis caused by genetic instability, t