Nuclear magnetic resonance (NMR) spectroscopy has considerable potential for non-invasive characterisation of tissue biochemistry and the diagnosis of tissue abnormalities, ranging from focal lesions in the brain, to tumours in any area of the body to assessing effect of HIV damage. However, the realisation of the full clinical potential NMR spectroscopy will depend on extracting information from the spectra directly and specifically related to the biochemistry of different tissue types under various normal and pathological circumstances. This paper reviews the progress made in the application of neural network analysis to the automatic characterisation of NMR data, raising some key issues and providing a perspective of the future of this technology.