In this paper, we consider the benefits of applying support vector machines (SVMs), radial
basis function (RBF) networks, and self-organizing maps (SOMs) for breast cancer detection …

Noninvasive optical imaging technology has the potential to improve the accuracy of
disease detection and predict treatment response. Pathology provides the critical link …

We explored the use of diffuse reflectance spectroscopy in the ultraviolet-visible (UV-VIS)
spectrum for the diagnosis of epithelial pre-cancers and cancers in vivo. A physical model …

Abstract Machine learning approaches were employed for malignant breast tumour
diagnosis and evaluation of the prognostic risk of recrudescence and metastasis by using …

This paper reports the development of a probability-based spectroscopic diagnostic
algorithm capable of simultaneously discriminating tumor core and tumor margins from …

Although conventional autofluorescence spectroscopy, in which fluorescence emission
spectra are recorded for fixed excitation wavelengths, has demonstrated good performance …

In this paper, we consider the benefits of applying support vector machines (SVMs) and
radial basis function (RBF) for breast cancer detection. The Wisconsin diagnosis breast …

Metal nanoshells have found promising applications in biomedical imaging and cancer
therapy. To facilitate the application of nanoshells in scattering based imaging techniques, it …

The ability of multi-modal optical spectroscopy to detect signals from pancreatic tissue was
demonstrated by studying human pancreatic cancer xenografts in mice and freshly excised …

Fluorescence Spectroscopy provides a non-invasive tool for real time diagnosis of cervical
pre-cancer. An important issue involved is to classify diseased tissue from normal using …