Acceptance of claims made in scientific research articles depends on the stance authors
take and their resources for appraisal (Martin and White, http://www. grammatics …

We report the application of a support vector machine (SVM) for the development of
diagnostic algorithms for optical diagnosis of cancer. Both linear and nonlinear SVMs have …

Pulsed laser‐induced autofluorescence spectroscopic studies of pathologically certified
normal, premalignant, and malignant oral tissues were carried out at 325 nm excitation. The …

Background and Objectives A probability‐based, robust diagnostic algorithm is an essential
requirement for successful clinical use of optical spectroscopy for cancer diagnosis. This …

In this paper, a hybrid neural network/genetic algorithm technique is presented, aiming at
designing a feature extractor that leads to highly separable classes in the feature space. The …

Abstract The influence of Artificial Intelligence (AI) is huge on the present young generation.
Especially Gen Y and Gen Z are not only using AI-related applications in their daily lives, but …

Abstract Background and Objectives Use of laser induced fluorescence (LIF) spectroscopy
for the diagnosis of cancer requires an appropriate diagnostic algorithm for spectral pattern …

We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-
vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the …

An aglorithm based on support vector machines (SVM), the most recent advance in pattern
recognition, is presented for use in classifying light-induced autofluorescence collected from …

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