𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Classification of tumour 1H NMR spectra by pattern recognition

✍ Scribed by S. L. Howells; R. J. Maxwell; J. R. Griffiths


Publisher
John Wiley and Sons
Year
1992
Tongue
English
Weight
536 KB
Volume
5
Category
Article
ISSN
0952-3480

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Generalization performance using backpro
✍ N.M. Branston; R.J. Maxwell; S.L. Howells πŸ“‚ Article πŸ“… 1993 πŸ› Elsevier Science βš– 354 KB

'H nuclear magnetic resonance spectroscopy enables many metabolites in normal and tumour tissue to be examined and has considerable clinical potential. However, the spectra are complex and much of the biochemical information they contain is inaccessible to visual analysis. This paper assesses the tr

Pattern recognition analysis of 1H NMR s
✍ Ross J. Maxwell; Irene MartΓ­nez-PΓ©rez; SebastiΓ‘n CerdΓ‘n; Miquel E. CabaΓ±as; Carl πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 820 KB

## Abstract Pattern recognition techniques (factor analysis and neural networks) were used to investigate and classify human brain tumors based on the ^1^H NMR spectra of chemically extracted biopsies (n = 118). After removing information from lactate (because of variable ischemia times), unsupervi

Towards a method for automated classific
✍ A. R. Tate; J. R. Griffiths; I. MartΓ­nez-PΓ©rez; Γ€. Moreno; I. Barba; M. E. CabaΓ± πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 300 KB

Recent studies have shown that MRS can substantially improve the non-invasive categorization of human brain tumours. However, in order for MRS to be used routinely by clinicians, it will be necessary to develop reliable automated classification methods that can be fully validated. This paper is in t